Abstract: Autorka Liz Rice, wiceprezydent działu Open Source Engineering w firmie Aqua Security, pokazała, jak w systemie Linux zostały skonstruowane komponenty, na podstawie których są najczęściej tworzone kontenery. Dzięki tej książce zrozumiesz, co się dzieje podczas wdrażania kontenerów i poznasz potencjalne niebezpieczeństwa zagrażające Twoim wdrożeniom. Jeżeli za pomocą poleceń kubectrl lub docker uruchamiasz aplikacje w kontenerach i używasz poleceń powłoki systemu Linux, takich jak ps i grep, masz wiedzę wystarczającą do rozpoczęcia lektury.

Abstract: Responsible Generative AI and Local LLMs Learning Generative AI During Live Coding This video series covers mastering the theory of Generative AI and using local LLMs like Mistral, llamafile, Candle, and Lorax. Lessons covered include: Profit Sharing Concepts Tragedy of the Commons Game Theory and Generative AI Perfect Competition Negative Externalities Fine-tuning Mistral with Ludwig Getting Started with llamafile Hello World in Candle Exploring Rust and Candle Transcribing Audio with Whisper Rust for LLMs Learning Objectives Learn about responsible and ethical uses of generative AI Getting hands-on with local LLMs like Mistral, llamafile, Candle, and Lorax Learning to build solutions by coding along during tutorials Learning the key syntax and features of the Rust Language Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: To drugie wydanie bestsellerowego przewodnika po technikach uczenia maszynowego. Wystarczą minimalne umiejętności programistyczne, aby dzięki tej książce nauczyć się budowania i trenowania głębokiej sieci neuronowej. Zawarto tu minimum teorii, a proces nauki jest ułatwiony przez liczne przykłady i ćwiczenia. Wykorzystano gotowe rozwiązania i przedstawiono zasady pracy ze specjalistycznymi narzędziami, w tym z TensorFlow 2, najnowszą odsłoną modułu. W efekcie niepostrzeżenie przyswoisz niezbędny zasób pojęć i narzędzi służących do tworzenia systemów inteligentnych. Poznasz różnorodne techniki i zaczniesz samodzielnie ich używać. Po lekturze będziesz biegle posługiwać się najnowszymi technologiami sztucznej inteligencji!

Abstract: Ta książka jest szerokim, aktualnym i praktycznym przeglądem metod analizy szeregów czasowych, w którym ujęto pełny potok przetwarzania danych czasowych i modelowania. Zaprezentowano w niej rzeczywiste przypadki użycia tych metod i zilustrowano je obszernymi fragmentami znakomicie zaprojektowanego kodu w językach R i Python. Znalazły się tutaj praktyczne wskazówki ułatwiające rozwiązywanie najczęstszych problemów występujących w inżynierii danych czasowych i ich analizie. Ujęto tu zarówno konwencjonalne metody statystyczne, jak i nowoczesne techniki uczenia maszynowego. To bardzo przydatny przewodnik, dzięki któremu analitycy danych, inżynierowie oprogramowania i naukowcy będą mogli płynnie przejść od podstaw pracy z szeregami czasowymi do rozwiązywania konkretnych zagadnień na profesjonalnym poziomie.

Abstract: Kubernetes jest platformą do orkiestracji kontenerów. Projekt ten należy dziś do najpopularniejszych i najbogatszych narzędzi w swojej klasie, stanowi także podstawę dla wielu innych platform, znanych jako systemy typu PaaS. Dzięki nim Kubernetes zyskał możliwość tworzenia aplikacji, jednak tego rodzaju narzędzia wymagają od programistów i architektów zastosowania odpowiednich wzorców projektowych. Opisują one schematy rozwiązywania problemów na różnych poziomach dokładności, a tym samym umożliwiają efektywne projektowanie i implementację nowoczesnych, elastycznych natywnych aplikacji chmurowych w Kubernetesie.

Abstract: Frameworki bardzo ułatwiają życie programistom. Pozwalają na szybkie tworzenie nawet rozbudowanych aplikacji, ale praca z frameworkiem najczęściej oznacza duże ograniczenia w doborze technologii. Wszystko jest w porządku, dopóki deweloper stosuje dokładnie te rozwiązania, które zaplanowali twórcy frameworka. Jeśli jednak zechce użyć innej bazy danych albo wykorzystać własną, autorską metodę uwierzytelniania użytkowników, może napotkać różne nieprzewidziane problemy. Szczęśliwie nie wszystkie mikrośrodowiska zachowują się w ten sposób. Framework napisany w Pythonie Flask, w odróżnieniu od typowych frameworków, umożliwia swobodne dobieranie technologii i komponentów aplikacji, a nawet tworzenie własnych rozwiązań. Oznacza to, że Flask pozwoli Ci zachować pełną kontrolę nad budowanym oprogramowaniem!

Abstract: Ta książka została napisana z myślą o doświadczonych programistach. Podstawowe zagadnienia, takie jak klasy, polimorfizm i kolekcje, znalazły się w kilku pierwszych rozdziałach, jednak zrozumienie treści całej publikacji wymaga umiejętności technicznych. Została poświęcona ważnym koncepcjom C# i tajnikom tego języka, które rzadko kiedy są opisywane w literaturze. Dokładnie omówiono tu typy ogólne, LINQ oraz techniki programowania asynchronicznego. Przedstawiono najnowsze możliwości platformy .NET Core i języka C# 8.0, takie jak strumienie asynchroniczne, referencje akceptujące wartości puste, dopasowywanie wzorców, domyślne implementacje interfejsów, zakresy, a także nową składnię indeksowania oraz zmiany w narzędziach platformy .NET. Liczne rozbudowane przykłady stanowią świetne uzupełnienie prezentowanych treści.

Abstract: To książka przeznaczona dla programistów, którzy chcą maksymalnie wykorzystać możliwości Kubernetesa, również poprzez pisanie własnych zasobów. W praktyczny sposób pokazuje, jak rozwijać natywne, działające w chmurze aplikacje dla Kubernetesa. Wyjaśnia, w jaki sposób działa biblioteka API client-go i jak należy budować zasoby niestandardowe. Znalazło się tu obszerne i szczegółowe omówienie interfejsu programowania i działania platformy Kubernetes, a także pisania stabilnego oprogramowania w języku Go. Nie zabrakło szeregu wskazówek dotyczących samego pisania kodu oraz przeprowadzania testów. Dużo uwagi poświęcono niestandardowym zasobom, kontrolerom, webhookom i niestandardowym serwerom API oraz wzorcom rozszerzania Kubernetesa.

Abstract: Przedsiębiorstwa z branży technologicznej ciągle mierzą się z silną konkurencją. Nietrudno zrozumieć, co stanowi o przewadze firmy niezależnie od branży czy wielkości. Wygrywanie wymaga utrzymywania przewagi konkurencyjnej, jaką jest zdolność określania, wdrażania i osiągania poziomów wydajności nieosiągalnych dla konkurencji. Najczęściej przewaga konkurencyjna ma dwa źródła. Pierwszym jest dostarczanie funkcjonalnych rozwiązań, które dają radość użytkownikom. Drugim — wykorzystywanie właściwych danych do wdrażania odpowiedniej strategii, która wciąż podlega optymalizacji. Zastosowanie w tych działaniach rozwiązań z dziedziny sztucznej inteligencji znacznie przyczynia się do sukcesu firmy.

Abstract: Ta książka jest podręcznikiem dla praktyków. Zawiera zbiór narzędzi, katalog metod, przewodnik ułatwiający pracę, mnóstwo przykładów i studiów przypadku. Znalazły się tutaj również jasne wskazówki dotyczące przeprowadzania procesu projektowania usług. Opisano, jak łatwo doprowadzić środowiska biznesowe i specjalistów od projektowania do współpracy. Po ogólniejszym omówieniu procesu ustanawiania i realizowania inicjatyw w zakresie projektowania usług zaprezentowano także szczegóły facylitacji przedsięwzięcia i kształtowania jego otoczenia. Wiele spośród uwzględnionych w tekście metod i narzędzi zostało już dobrze opisanych. Tutaj natomiast, poza ich prezentacją, dodano szereg wskazówek i porad najlepszych ekspertów w dziedzinie projektowania usług. W ten sposób umożliwiono powiązanie doświadczenia z działalnością operacyjną i sukcesem biznesowym oraz budowaniem kultury klientocentryzmu.

Abstract: To kompleksowy podręcznik do nauki programowania w Pythonie. Jego piąte wydanie zostało gruntownie zaktualizowane i rozbudowane o dodatkowe treści. Omówiono tu najnowsze wersje Pythona w liniach 3.X i 2.X, czyli 3.3 i 2.7, i dodano opisy nowych lub rozszerzonych mechanizmów, takich jak obsługa formatu JSON, moduł timeit, pakiet PyPy, metoda os.popen, generatory, rekurencje, słabe referencje, atrybuty i metody __mro__, __iter__, super, __slots__, metaklasy, deskryptory, funkcja random, pakiet Sphinx i wiele innych. W książce znalazło się mnóstwo ćwiczeń, quizów, pomocnych ilustracji oraz przykładów kodu. Jest to kompendium dla każdego, kto chce szybko zacząć programować w Pythonie i tworzyć wydajny kod o wysokiej jakości.

Abstract: Ta książka jest przeznaczona dla średnio zaawansowanych i początkujących programistów, którzy chcą poznać narzędzia ułatwiające tworzenie różnych aplikacji w JavaScripcie. Przedstawiono tu kompletne instrumentarium, dzięki któremu można tworzyć kod aplikacji w stylu CRUD działającej na każdej platformie. Opisano, w jaki sposób należy przygotować sobie środowisko programistyczne do pracy, omówiono sposób tworzenia API za pomocą Node i Express, bazy danych MongoDB oraz serwera Apollo. Sporo miejsca poświęcono tworzeniu interfejsów użytkownika niezależnych od platformy za pomocą różnych narzędzi. Poszczególne zagadnienia zilustrowano praktycznymi przykładami działającego kodu. Dzięki tej publikacji nawet początkujący programista zacznie szybko podejmować świadome decyzje technologiczne.

Abstract: Z tego zwięzłego przewodnika po technikach uczenia maszynowego opartego na strukturalnych danych skorzystają programiści, badacze, osoby zajmujące się nauką o danych oraz twórcy systemów sztucznej inteligencji. Znalazł się tu wyczerpujący opis procesu uczenia maszynowego i klasyfikacji danych strukturalnych. Przedstawiono też metody klastrowania danych, analizy regresji, redukcji wymiarowości oraz inne ważne zagadnienia. Prezentowane treści zostały zilustrowane uwagami, tabelami i przykładami kodu. Nie zabrakło opisu przydatnych bibliotek, niezwykle użytecznych w pracy analityka danych. W efekcie książka pozwala na szybkie rozwiązywanie różnego rodzaju problemów związanych z przetwarzaniem danych strukturalnych.

Abstract: Dzięki tej książce dowiesz się, jak sobie z tym poradzić. Znalazło się w niej krótkie wprowadzenie do Pythona oraz do automatyzacji przetwarzania tekstu i obsługi systemu plików, a także do pisania własnych narzędzi wiersza poleceń. Zaprezentowano również przydatne narzędzia linuksowe, systemy zarządzania pakietami oraz systemy budowania, monitorowania i automatycznego testowania kodu. Zagadnienia te szczególnie zainteresują specjalistów DevOps. Ponadto zawarto tu podstawowe informacje o chmurze obliczeniowej, usługach IaC i systemach Kubernetes. Omówiono zasady uczenia maszynowego i inżynierii danych z perspektywy DevOps. Przedstawiono także kompletny przewodnik po procesach budowania, wdrażania oraz operacyjnego wykorzystywania modelu uczenia maszynowego z użyciem systemów Flask, sklearn, Docker i Kubernetes.

Abstract: Interactive Technical Projects A weekly updated series of tutorials on interactive technical projects Learning Objectives Learn practical skills by building real-world projects with cutting-edge technologies Learning to build full stack solutions with languages like Rust, Python, LLMs and Data Science Learning the key tools and techniques used by industry experts to create robust applications Get hands-on practice applying your core technical knowledge Understand how all the pieces fit together by building projects end-to-end Troubleshoot bugs and solve complex problems that appear in production systems Expand your portfolio and r©♭sum©♭ with impressive projects Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: MySQL for Data Engineering Learning Linux Hacker Style Coding Description: Extract MySQL data through queries and bash pipelines Dump query results to CSV files. Build web services to serve data with Python standard library Analyze and process extracts with Linux utilities Chain MySQL, Python, and Linux together for quick data tasks Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: GenAI and LLMs on AWS Learn to build machine learning pipelines leveraging large language models on AWS for natural language processing and generative AI. In this hands-on course, you will gain skills to: * Set up cloud-based Rust development environments * Construct serverless workflows with AWS Lambda and Step Functions * Generate text and code with models like Claude and CodeWhisperer * Orchestrate models and data workflows with Amazon Bedrock * By completing real-world coding projects, you will be prepared to operationalize LLMs for machine learning applications. Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Agile with AI Enhancing Agile Methodologies with Artificial Intelligence This video course explores the integration of Agile practices with Artificial Intelligence (AI) to streamline software development processes and improve productivity. By combining the principles of Agile and the capabilities of AI, you can unlock new levels of efficiency and innovation. Lessons Covered Include: 1.0 Course Introduction 2.1 Waterfall Planning 2.2 Playground vs. Plant Analogy 3.2 Pragmatic Agile 3.15 Productivity Techniques 4.1 AIOps (Artificial Intelligence for IT Operations) 4.2 Diagram Prompt Engineering 4.3 Summarizing Text with Claude 4.4 AI Pair Programming: Paradigm Shift 4.5 AWS CodeWhisperer for Rust 4.7 Serverless Bedrock Diagram 4.8 Bedrock Knowledge Agent: Retrieval-Augmented Generation (RAG) 4.9 Building Blocks for Generative AI: WhisperCPP RAW Learning Objectives Understand the foundations of Agile methodologies and their importance in software development Learn techniques for enhancing Agile practices with AI tools and techniques Explore AI-powered productivity techniques for streamlining development workflows Discover AI-driven approaches to pair programming, code generation, and prompt engineering Gain insights into cutting-edge AI applications in software development, such as AIOps and knowledge agents Learn to leverage AI tools like AWS CodeWhisperer and Retrieval-Augmented Generation (RAG) models Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Small Language Models and LLamaFile Learning About Small Language Models and Running Them Locally with LLamaFile This video series covers small language models, their advantages, and how to run them locally using the LLamaFile tool. Lessons Covered Include: 1.1 Introduction to Small Language Models 1.2 Demo: Running Phi Small Language Model with LLamaFile 2.1 Getting Started with LLamaFile 2.2 Demo: Running Lava Multi-Modal Vision Model with LLamaFile Learning Objectives Understand what small language models are and their advantages Learn how to run local language models using the LLamaFile tool See demos of running different small language models like Phi and Lava Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Many organizations today have begun to modernize their Windows workloads to take full advantage of cloud economics. If you're a C# developer at one of these companies, you need options for rehosting, replatforming, and refactoring your existing .NET Framework applications. This practical book guides you through the process of converting your monolithic application to microservices on AWS. Authors Noah Gift, founder of Pragmatic AI Labs, and James Charlesworth, engineering manager at Pendo, take you through the depth and breadth of .NET tools on AWS. You'll examine modernization techniques and pathways for incorporating Linux and Windows containers and serverless architecture to build, maintain, and scale modern .NET apps on AWS. With this book, you'll learn how to make your applications more modern, resilient, and cost-effective. Get started building solutions with C# on AWS Learn DevOps best practices for AWS Explore the development tools and services that AWS provides Successfully migrate a legacy .NET application to AWS Develop serverless .NET microservices on AWS Containerize your .NET applications and move into the cloud Monitor and test your AWS .NET applications Build cloud native solutions that combine the best of the .NET platform and AWS.

Abstract: Databricks Certified Data Engineer Associate Course 1: Databricks Lakehouse Platform Description Learn foundational Databricks capabilities including compute, storage, notebooks, and jobs to build scalable data solutions. Learning Objectives Create clusters and configure runtime environments Perform exploratory analysis with notebooks Schedule and monitor multi-task workflows Course 2: Databricks SQL Description Master Spark SQL for reading, transforming, and loading data at scale. Learn techniques like data validation, custom business logic, and slowly changing dimensions. Learning Objectives Query data in notebooks with Spark SQL Handle complex data types Apply data quality rules Implement slowly changing dimensions Course 3: Databricks ML Description Build ML models with Python and Scala APIs in Databricks. Learn best practices for feature engineering, hyperparameter tuning, and model evaluation. Learning Objectives Engineer features from raw data Tune models with cross validation Evaluate model performance Operationalize models with MLflow Course 4: Databricks Data Engineering Description Architect reliable and performant data infrastructure with Delta Lake, streaming, and autoscaling. Learning Objectives Implement ACID transactions Build streaming ETL solutions Autoscale infrastructure to meet SLAs Migrate data warehouses to lakehouse Course 5: Workloads with Jobs Description Orchestrate workloads using multi-task Jobs with configurable scheduling, dependencies, and error handling. Learning Objectives Schedule notebooks, jobs and pipelines Set dependencies across tasks Handle and retry failures Monitor runs using the Jobs UI Course 6: Data Access with Unity Catalog Description Provide governed data access across storage like ADLS, S3, and GCS using Unity Catalog. Learning Objectives Deploy a Unity Catalog Manage credentials securely Apply object-level security Query data from storage tiers Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production. Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs. You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you: Learn the MLOps process, including its technological and business value Build and structure effective MLOps pipelines Efficiently scale MLOps across your organization Explore common MLOps use cases Build MLOps pipelines for hybrid deployments, real-time predictions, and composite AI Learn how to prepare for and adapt to the future of MLOps Effectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy.

Abstract: Kubernetes has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help. Using Kubernetes as your platform, you'll discover open source technologies that are designed and built for the cloud. Delve into case studies to avoid the pitfalls others have faced and explore new use cases. Get an insider's view of what's coming from the innovators who are creating next-generation architectures and infrastructure. And you'll learn how to: Manage different data use cases on Kubernetes Reduce costs and simplify application development Leverage data and infrastructure to create new use cases and business models Make data infrastructure choices that are cost-efficient, secure, scalable, and elastic And more

Abstract: As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas. Refine a question of interest to one that can be studied with data Pursue data collection that may involve text processing, web scraping, etc. Glean valuable insights about data through data cleaning, exploration, and visualization Learn how to use modeling to describe the data Generalize findings beyond the data

Abstract: Rust Data Engineering: Course Description Are you a data engineer, software developer, or a tech enthusiast with a basic understanding of Rust, seeking to enhance your skills and dive deep into the realm of data engineering with Rust? Or are you a professional from another programming language background, aiming to explore the efficiency, safety, and concurrency features of Rust for data engineering tasks? If so, this course is designed for you. While a fundamental knowledge of Rust is expected, you should ideally be comfortable with the basics of data structures and algorithms, and have a working understanding of databases and data processing. Familiarity with SQL, the command line, and version control with git is advantageous. This four-week course focuses on leveraging Rust to create efficient, safe, and concurrent data processing systems. The journey begins with a deep dive into Rust's data structures and collections, followed by exploring Rust's safety and security features in the context of data engineering. In the subsequent week, you'll explore libraries and tools specific to data engineering like Diesel, async, Polars, and Apache Arrow, and learn to interface with data processing systems, REST, gRPC protocols, and AWS SDK for cloud-based data operations. The final week focuses on designing and implementing full-fledged data processing systems using Rust. By the end of this course, you will be well-equipped to use Rust for handling large-scale data engineering tasks, solving real-world problems with efficiency and speed. The hands-on labs and projects throughout this course will ensure you gain practical experience, putting your knowledge into action. This course is your gateway to mastering data engineering with Rust, preparing you for the next level in your data engineering journey. Learning Rust During Live Coding This video series covers live coding the Rust language iteratively, thus learning the language. Lessons Covered Include: Section 1: Rust Data Structures: Collections Lesson 1: Getting Started With The Modern Rust Development Ecosystem Meet the instructor & Course Overview: 1.0-meet-instructor-course-overview.mp4 Introduction to the AI Coding Paradigm Shift: 1.1-ai-pair-programming-paradigm-shift.mp4 Introduction to cloud-based development environments: 1.2-GitHub-Codespaces-Ecosystem-with-copilot-chat.mp4 Introduction to GitHub Copilot Ecosystem for Rust: 1.3-copilot-enabled-rust.mp4 Prompt Engineering with GCP BigQuery SQL: 1.4-big-query-prompt-engineering.mp4 Introduction to AWS CodeWhisperer for Rust: 1.5-aws-codewhisperer-for-rust.mp4 Using Google Bard to Enhance Productivity: 1.6-using-bard-to-enhance-productivity.mp4 Continuous Integration with Rust and GitHub Actions: 1.7-continuous-integration-rust-github-actions.mp4 Lesson 2: Rust Sequences and Maps Introducing Rust Sequences and Maps: 1.8-rust-sequences-maps.mp4 Print Rust data structures demo: 1.9-Print-Rust-data-structures-demo.mp4 Vector Fruit Salad demo: 1.10-Vector-Fruit-Salad-demo.mp4 VecDeque Fruit Salad demo: 1.11-VecDeque-Fruit-Salad-demo.mp4 Linkedin List Fruit Salad demo: 1.12-Linkedin-List-Fruit-Salad-demo.mp4 Fruit Salad CLI demo: 1.13-Fruit-Salad-CLI-demo.mp4 HashMap frequency counter demo: 1.14-HashMap-frequency-counter-demo.mp4 HashMap language comparison: 1.15-HashMap-language-comparison.mp4 Lesson 3: Rust Sets, Graphs and Miscellaneous Data Structures Analyzing UFC Fighter Network Using Graph Centrality in Rust: 1.16-ufc-graph-centrality.mp4 Storing Unique Fruits Using HashSet in Rust: 1.17-unique-fruits-with-hashset.mp4 Maintaining Sorted and Unique Fruits Using BTreeSet in Rust: 1.18-sorted-unique-fruits-with-btreeset.mp4 Creating a Fig Priority Fruit Salad Using Binary Heap in Rust: 1.19-fig-priority-fruit-salad-with-binary-heap.mp4 PageRank algorithm for sports data: 1.20-pagerank-sports.mp4 Showing shortest path with dijkstra: 1.21-shortest-path.mp4 Detecting Strongly Connected Components: A Deep Dive into Kosaraju's Algorithm: 1.22-strongly_connected_components_with_kosaraju.mp4 Simple Charting of Data Structures in Rust: 1.23-ascii-graphing.mp4 Section 2: Safety, Security and Concurrency with Rust Lesson 1: Rust Safety and Security Features Multi-Factor Authentication: 2.1_Multi-Factor_Authentication.mp4 Network Segmentation: 2.2_Network_Segmentation.mp4 Least Privilege Access: 2.3_Least_Privilege_Access.mp4 Encryption: 2.4_Encryption.mp4 Mutable fruit salad: 2.5-mutable-fruit-salad.mp4 Customize fruit salad with a CLI: 2.6-customize-csv-fruit-salad.mp4 Data Race example: 2.7-data-race.mp4 Lesson 2: Security Programming with Rust High Availability: 2.10-high-availability.mp4 Understanding the Homophonic Cipher: A Cryptographic Technique: 2.11-homphonic-cipher.mp4 Decoding the Secrets of the Caesar Cipher: 2.12-caesar-cipher.mp4 Building a Caesar Cipher Command Line Interface: 2.13-caesar-cipher-cli.mp4 Creating a Decoder Ring: A Practical Guide: 2.14-decoder-ring.mp4 Detecting Duplicates with SHA-3: A Data Integrity Tool: 2.15-sha3-dupe-detector.mp4 Incident Response: 2.16-incident-response.mp4 Compliance: 2.17-compliance.mp4 Lesson 3: Concurrency with Rust Core Concepts in Concurrency: 2.20-core-concepts-concurrency.mp4 Dining Philosophers: 2.21-dining-philosopher.mp4 Web Crawl Wikipedia with Rayon: 2.22-web-crawl-wikipedia-rayon.mp4 Intelligent Chatbot with Tokio: 2.23-tokio-chatbot.mp4 Multi-threaded deduplication with Rust: 2.24-data-eng-with-rust-dedupe.mp4 Energy Efficiency Python vs Rust: 2.25-energy-efficiency-python-rust.mp4 Concurrency Stress test with a GPU: 2.26-building-cuda-enabled-stress-test-with-rust-pytorch.mp4 Host Efficiency Serverless Optimization problem: 2.27-host-efficiency-optimization-problem.mp4 Section 3: Rust Data Engineering Libraries and Tools Lesson 1: Using Rust to Manage Data, Files and Network Storage Process CSV files in Rust: 2.31-process-csv-rust.mp4 Using Cargo Lambda with Rust: 2.33-cargo-lambda-rust.mp4 List files on AWS EFS with Rust: 2.34-rust-efs-lister.mp4 Use AWS S3 Storage: 2.35-use-s3-storage.mp4 Use AWS S3 Storage from Rust: 2.36-use-rust-for-s3-storage.mp4 Write encrypted data to tables or Parquet files: 2.37-Write-encrypted-data-to-tables-or-Parquet-files.mp4 Lesson 2: DataFrames with Rust, Python and Notebooks What is Colab?: 2.40-what-is-colab.mp4 Using Bard to enhance notebook development: 2.41-using-bard-to-enhance-productivity.mp4 Exploring Life Expectency in a Notebook: 2.42-life-expectancy-eda.mp4 Load a DataFrame with sensitive data: 2.43-Load-a-DataFrame-with-sensitive-information.mp4 Using MLFlow with Databricks Notebooks: 2.44-mlops-mlflow-tracking.mp4 End to End ML with MLFlow and Databricks: 2.45-end-to-end-ml-with-mlflow-and-databricks.mp4 Comparing DataFrame Libraries between Rust and Python: 2.46-comparing-dataframe-libs-rust-python.mp4 Lesson 3: Data Engineering Libraries and Tools with Rust Parquet file writing and reading with Rust: 2.50-parquet-read-write-rust.mp4 Arrow & Parquet in Rust: 2.51-arrow-parquet-rust.mp4 Serverless functions with Rust and AWS Lambda: 2.52-serverless-rust-aws-lambda.mp4 Polars library overview: 2.53-polars-library-overview.mp4 Building RESTful APIs with Rocket: 2.54-building-restful-apis-rocket.mp4 Utilizing Async Rust in Web Development: 2.55-utilizing-async-rust-web-development.mp4 Applying Data Cleaning Techniques with Rust: 2.56-applying-data-cleaning-rust.mp4 Deploying Rust Applications in a Kubernetes Environment: 2.57-deploying-rust-apps-kubernetes.mp4 Section 4: Designing Data Processing Systems in Rust Lesson 1: Getting Started with Rust Data Pipelines (Including ETL) Jack and the Beanstalk Data Pipelines: 4.1-jack-beanstalk-building-data-pipelines.mp4 Open Source Data Engineering - Pros and Cons: 4.2-open-source-de-pro-con.mp4 Core Components of Data Engineering Pipelines: 4.3-core-components-data-engineering-pipelines.mp4 Rust AWS Step Functions Pipeline: 4.4-rust-aws-step-functions.mp4 Rust AWS Lambda Async S3 Size Calculator: 4.5-rust-async-s3-size-calculator-lambda.mp4 What is Distroless: 4.6-what-is-distroless.mp4 Demo Deploying Rust Microservices on GCP: 4.7-demo-build-deploy-rust-microservice-cloud-run.mp4 Lesson 2: Using Rust and Python for LLMs, ONNX, Hugging Face, and PyTorch Pipelines Introduction to Hugging Face Hub: 4.10-intro-hugging-face-hub.mp4 Rust PyTorch Pre-trained Model Ecosystem: 4.11-rust-pytorch-pretrained-models-ecosystem.mp4 Rust GPU Hugging Face Translator: 4.12-rust-gpu-hugging-face-translator.mp4 Rust PyTorch High-Performance Options: 4.13-high-performance-pytorch-rust-demo.mp4 Rust CUDA PyTorch Stress Test: 4.14-building-cuda-enabled-stress-test-with-rust-pytorch.mp4 EFS ONNX Rust Inference with AWS Lambda: 4.15-efs-onnx-lambda-rust-inference-mlops.mp4 Theory behind model fine-tuning: 4.16-intro-fine-tuning-theory.mp4 Doing Fine Tuning: 4.17-doing-fine-tuning.mp4 Lesson 3: Building SQL Solutions with Rust, Generative AI and Cloud Selecting the correct database on GCP: 4.20-gcp-optimize-d...

Abstract: Learning Generative AI with AWS CodeWhisperer During Live Coding This video series covers live coding in various languages iteratively, thus learning the language. Lessons Covered Include 1.0 Getting started with Bash and Rust using AWS CodeWhisperer, VSCode, and AWS Toolkit for VSCode Learning Objectives Learn the fundamentals of Generative AI Learn to build AI-powered solutions with Bash, Rust, and AWS services Master the key syntax and features of Bash and Rust languages Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Live Coding in Rust: Unleash the Power of Systems Programming Delve deep into the Rust ecosystem with this groundbreaking live coding series, focused on building robust and performant software, including cutting-edge topics like LLMOps and machine learning with Hugging Face's Candle library. What You'll Get Live coding sessions with expert commentary Weekly updates and continually expanding! High-impact projects and examples Exclusive discussions on Rust best practices Topics covering LLMOps, machine learning, and more A focus on performance, safety, and systems programming Course Outline (Future and Current Content) Rust Fundamentals Introduction to Rust Understanding Ownership & Borrowing Error Handling in Rust LLMOps in Rust Live Coding Rust: LLMOps in Rust--Exploring Hugging Face Candle Building Custom LLMOps Libraries Rust and LLVM: A Match Made in Heaven Machine Learning in Rust Implementing ML Algorithms in Rust Using Hugging Face Candle for NLP Deploying Rust ML Models in Production Systems Programming Writing File Systems in Rust Creating Web Servers with Actix Asynchronous Programming with async/await Rust in DevOps Automating CI/CD Pipelines with Rust Rust for Cloud Operations Rust in Containerized Environments Topics Covered LLMOps : The intersection of LLVM and DevOps Machine Learning : Building and deploying models in Rust Systems Programming : Low-level operations made easier and safer DevOps : Leverage Rust for automating operations tasks Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Rust LLMOps: A Rough Draft Course (Updated JIT) Learning During Live Coding This video series is a rough draft course being updated JIT (Just in Time) and covers the Rust language through live coding. We offer an iterative approach to understand and master the language, particularly focusing on its application in MLOps. Lessons Covered Include: Rust Hugging Face Candle Description This week, you will delve into the powerful combination of Rust with Candle, a minimalist ML framework, and explore how they can be used with Hugging Face's popular transformer models. You will apply these concepts by working on a series of hands-on labs that guide you through building, training, and deploying machine learning models using Rust, Candle, and Hugging Face. Learning Objectives By the end of this lesson, you will be able to: - Implement Candle in Rust to create and train machine learning models. - Utilize the various features of Candle, including syntax, GPU efficiency, and browser deployment. - Integrate Hugging Face transformers with Rust for natural language processing tasks. - Apply the principles of Rust and Candle to build real-world machine learning applications. - Evaluate the performance and scalability of Rust-based ML solutions using Candle and Hugging Face. Lesson Structure Original 4.1 Candle: A Minimalist ML Framework for Rust 4.2 Using GitHub Codespaces for GPU Inference with Rust Candle 4.3 VSCode Remote SSH development AWS Accelerated Compute 4.4 Building Hello World Candle 4.5 Exploring StarCoder: A State-of-the-Art LLM for Code 4.6 Using Whisper with Candle to Transcribe 4.7 Exploring Remote Dev Architectures on AWS.

Abstract: GitHub Enterprise - Certified Learning the GitHub Enterprise Certification Material This course covers all seven domains of the the GitHub Enterprise Certification Lessons Covered Include: Domain 1: Support GitHub Enterprise for users and key stakeholders Distinguish admin tasks vs needing GitHub Support Generate support bundles and diagnostics Identify underutilized features, integrations, active teams/repos Recommend standards for workflows, branching, code review, automation Explain tooling ecosystem and CI/CD strategy Recommend workflows and tooling to teams Use GitHub APIs to extend admin capabilities Find Marketplace assets for specific needs Contrast GitHub Apps vs actions Domain 2: Manage user identities and GitHub authentication Implications of enabling SAML SSO for orgs/enterprise Steps to enable and enforce SAML SSO Require two-factor authentication Supported identity providers GitHub identity management and authorization Authentication and authorization model Supported SCIM providers How SCIM and team sync works Domain 3: Describe deployment, distribution, licensing Capabilities of GHES, GHEC, GHAE Billing models including licenses, Actions, Packages License usage statistics for orgs, enterprise, machine accounts Consumption of metered products Domain 4: Manage access and permissions Enterprise permissions and policies Organization permissions Team permissions Repository permissions Domain 5: Enable secure development and compliance How GitHub supports enterprise security Scrubbing sensitive data Choosing policies for control required Impacts of policies Organization and enterprise policies Use audit log APIs to explain missing assets Security features of GitHub repositories Create security response plan SSH keys and deploy keys Domain 6: Manage GitHub Actions Distribute actions and workflows in enterprise Manage runners Manage encrypted secrets Domain 7: Manage GitHub Packages Supported Packages Accessing, writing, and sharing Packages Using Packages in workflows Contrasting Packages and releases Learning Objectives Manage user access and permissions across GitHub Enterprise environments through authentication, organizations, teams, and repositories. Establish secure development practices and compliance controls with GitHub features. Distribute and manage GitHub Actions across the enterprise. Additional Popular Resources 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Analytics projects are frequently long-drawn-out affairs, requiring multiple teams and skills to clean, join, and eventually turn data into analysis for timely decision-making. Alteryx Designer changes all of that. With this low-code, self-service, drag-and-drop workflow platform, new and experienced data and business analysts can deliver results in hours instead of weeks. This practical book shows you how to master all areas of Alteryx Designer quickly. Author and Alteryx ACE Joshua Burkhow starts with the basics of building a workflow, then introduces more than 200 tools for working with intermediate and advanced analytics functionality. With Alteryx Designer's all-in-one toolkit, you'll migrate from legacy analytics software or Excel with ease. Ready to work with data quickly and efficiently? This guide gets you started. Learn the fundamentals of cleaning, prepping, and analyzing data with Alteryx Designer Install, navigate, and quickly become competent with the Alteryx Designer layout and functionality Construct accurate, performant, reliable, and well-documented workflows that automate business processes Learn intermediate techniques using spatial analytics, reporting, and in-database tools Dive into advanced Alteryx capabilities, including predictive and machine learning tools Get introduced to the entire Alteryx Analytic Process Automation (APA) Platform

Abstract: Advances in machine learning techniques, the cloud, and the ability to leverage hardware acceleration have changed the way we work with data — adding entirely new capabilities and business models to the mix. But the demand for processing training data has outpaced the increase in computation power. This practical and comprehensive guide will show you how to distribute your machine learning workload across multiple machines and turn centralized systems into distributed ones. Machine Learning with Spark examines various technologies for building end-to-end distributed machine learning platforms based on the Apache Spark ecosystem with Spark MLlib, TensorFlow, Horovod, PyTorch, and more. This book shows you when to use each technology and why. You'll also learn how to: Build efficient parallelization of the training process Create a coherent model Leverage a set of open source tools to build scalable end-to-end ML platform Enable more advanced, tailor-made products Use distributed ML techniques to increase the quality of predictions and ML modules Design practical distributed machine learning systems

Abstract: Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, authors Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while avoiding single points of failure and manual scheduling. If your data processing has grown beyond what a single computer can handle, this book is for you. Written by experienced software architecture practitioners, Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness. This book covers distributed processing (the pure Python implementation of serverless) and shows you how to: Implement stateful applications with Ray actors Build workflow management in Ray Use Ray as a unified platform for batch and streaming Implement advanced data processing with Ray Apply microservices with Ray platform Implement reliable Ray applications

Abstract: Get started with Ray, the open source distributed computing framework that greatly simplifies the process of scaling compute-intensive Python workloads. With this practical book, Python programmers, data engineers, and data scientists will learn how to leverage Ray locally and spin up compute clusters. You'll be able to use Ray to structure and run machine learning programs at scale. Authors Max Pumperla, Edward Oakes, and Richard Liaw show you how to build reinforcement learning applications that serve trained models with Ray. You'll understand how Ray fits into the current landscape of data science tools and discover how this programming language continues to integrate ever more tightly with these tools. Distributed computation is hard, but with Ray you'll find it easy to get started. Learn how to build your first distributed application with Ray Core Conduct hyperparameter optimization with Ray Tune Use the Ray RLib library for reinforcement learning Manage distributed training with the RaySGD library Use Ray to perform data processing Learn how work with Ray Clusters and serve models with Ray Serve Build an end-to-end machine learning application with Ray

Abstract: Assimilate ONNX Learning about ML Model portability During Live Coding This video series covers live coding the Language iteratively thus learning the language. Lessons Covered Include: 1.0 Getting started with ONNX. In this live coding session I was able to get both resnet and ONNX working in Rust with Sonos/Trac. Learning Objectives Learn to work with ONNX models Learning to build solutions with ONNX models in Rust Learning the key syntax and features ONNX models Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: This video series covers live coding with TensorFlow and the Rust language.

Abstract: Google Professional Cloud Architect Certification Course 2023 (Rough Draft) Welcome to the Google Professional Cloud Architect Certification Course! This course is designed to help you prepare for the Google Cloud Certified Professional Cloud Architect certification exam. As a professional cloud architect, you will be responsible for designing, developing, and managing secure, scalable, and highly available cloud solutions using Google Cloud Platform. Course Overview Course One: Designing and planning a cloud solution architecture 1.0 Rough Draft Introduction Introduction to Google Professional Architect Course Onboarding to GCP Cloud Designing a solution infrastructure that meets business requirements Designing a solution infrastructure that meets technical requirements Designing network, storage, and compute resources Using Google Cloud Functions Running Minikube Running Minikube with FastAPI for Kubernetes development Getting Started with Google Cloud Run Load testing with locust Design technical solutions for evolution and migration SRE Mindset Conclusion and Next Steps Course Two: Managing and provisioning a solution infrastructure Introduction to Google Professional Architect Course Two Exploring Network Topologies in GCP: A Demonstration Embracing Hybrid Networking in Google Cloud Platform Overview of GCP Storage Demo of using the SDK and CLI to manage storage Data lifecycle management Data security Demo of building Rust deduplication finder Compute volatility configuration (preemptible vs. standard) Demo Build and Deploy Rust Actix Microservice Cloud Run Container orchestration with GKE Demo of extending Google Cloud Functions Conclusion Course Two Course Three: Designing for Security and Compliance Introduction to Google Professional Architect Course Three Mastering Identity and Access Management in GCP Data Security Best Practices for GCP Secrets Manager API: A Hands-on Guide Exploring a data poisoning attack Meeting Industry Certification Requirements in GCP Auditing GCP Security with Log Analysis Creating Custom Log Dashboards for GCP Security Monitoring Scanning Web Applications with GCP's Cloud Web Security Scanner Analyzing GCP Logs with BigQuery GCP Security: Conclusion and Next Steps Course Four: Designing and optimizing technical and business processes Introduction to Google Professional Architect Course Four Continuous Delivery: An Introduction Hands-on with Continuous Integration in GCP Troubleshooting Techniques: The Five Whys Implementing Simple GitHub Actions for CI/CD The Three Most Important Files in a Python Project Utilizing Trello for Effective Project Management Leveraging Spreadsheets for Project Management Exploring the MLOps Maturity Model Building Bespoke Systems for Core Business Functions Data Science on Windows: Virtualenv and Pip Site Reliability Engineering (SRE) in GCP Performing Load Testing in GCP: A Demo Course Five: Managing and optimizing cloud solution Implementation Introduction to Google Professional Architect Course Five Makefiles Made Easy: A Comprehensive Guide Configuring Your Bashrc for an Optimal Environment Implementing Continuous Integration for Rust with GitHub Actions Unit Testing in Rust: A Hands-on Demonstration Supercharging Rust Development with Copilot Setting Up a GCP Workstation for Python Development Mastering Google Cloud Shell: A Practical Guide Streamline Your Development with Google Cloud Editor Getting Started with the Google Cloud CLI SDK Unleashing the Power of Google Cloud's 'gcloud' Command-Line Tool Deploying Rust Applications to App Engine: A Step-by Course Six: Ensuring solution and operations reliability Introduction to Google Professional Architect Course Six Monitoring and Logging Rust App Engine Applications: A Demo Uncovering the Advantages of Cloud Developer Workspaces Operationalizing Microservices in the Cloud Introducing GitHub Codespaces for Streamlined Development Compiling Python Projects in GitHub Codespaces Mastering Continuous Integration in GCP Course Wrap-up and Future Steps in Your GCP Journey Learning Objectives Design and optimize cloud solutions Analyze and optimize technical and business processes Manage and provision cloud infrastructure Ensure solution and operations reliability By the end of this course, you will have the knowledge and skills needed to pass the Google Cloud Certified Professional Cloud Architect exam and to effectively design and manage cloud solutions using Google Cloud Platform. Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Certification Exam Guide Welcome to the Google Professional Machine Learning Engineer Course! This course is designed to help you prepare for the Google Professional Machine Learning Engineer certification exam. Learning Objectives Develop a deep understanding of Google Cloud technologies and various ML models and techniques to design, build, and productionize machine learning solutions that address specific business challenges while adhering to responsible AI practices. Collaborate effectively with cross-functional teams, including application developers, data engineers, and data governance professionals, to ensure the long-term success of ML models throughout their development, deployment, and maintenance. Master the skills required to design, implement, and manage ML architectures, data pipelines, and metric interpretations, as well as optimize model performance through training, retraining, deploying, scheduling, monitoring, and refining models in scalable and efficient ways. Learn how to use the Google Cloud Platform (GCP) to build and deploy ML models, including how to use GCP services such as BigQuery, Cloud Storage, Cloud AI Platform, and Cloud Functions to build and deploy ML models. Who Should Take This Course? Data scientists Data engineers Machine learning engineers Software engineers Data analysts Data architects Business analysts Anyone interested in learning about machine learning and Google Cloud Platform Course One: Framing ML Problems Course Two: Architecting ML solutions Course Three: Designing data preparation and processing systems Course Four: Developing ML models Course Five: Automating and orchestrating ML pipelines Course Six: Monitoring, optimizing, and maintaining ML solutions Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Professional Data Engineer Certification Course Section 1: Designing Data Processing Systems 1.1 Storage technology selection 1.2 Data pipeline design 1.3 Data processing solution design 1.4 Data warehousing & processing migration Section 2: Building & Operationalizing Data Processing Systems 2.1 Storage system implementation 2.2 Pipeline building & operationalization 2.3 Processing infrastructure implementation Section 3: Operationalizing ML Models 3.1 Pre-built ML models as a service 3.2 ML pipeline deployment 3.3 Training & serving infrastructure selection 3.4 ML model measurement, monitoring & troubleshooting Section 4: Ensuring Solution Quality 4.1 Security & compliance design 4.2 Scalability & efficiency assurance 4.3 Reliability & fidelity assurance 4.4 Flexibility & portability assurance Learning Objectives Learn to design, build, and operationalize data processing systems that meet business requirements, system requirements, and industry best practices. Learning to build scalable, efficient, and secure solutions with Google Cloud technologies to manage and analyze data at scale. Learning the key syntax and features of the SQL language for handling, querying, and performing operations on structured data in Google Cloud. Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Using Rust with Python A Practical Guide to Rust for Python Developers Topics: Lesson 1: Introduction to Rust and Python Integration & PyO3 Basics Video 1.1 : Introduction to Rust and Python Video 1.2 : PyO3 Installation Video 1.3 : Basic Rust Library Video 1.4 : Rust to Python Video 1.5 : Rust Ownership Model Video 1.6 : Diagram PyO3 Project Video 1.7 : Python Calc CLI Video 1.8 : PyO3 Features Video 1.9 : PyO3 Exceptions Lesson 2: Advanced Rust and Python Mixing Techniques Video 1.10 : Call Python from Rust Video 1.11 : Run Python Embedded in Rust Video 1.12 : Embedded Rust CLI Diagram Video 1.13 : Embedded Rust CLI Video 1.14 : Embedded Rust CLI Test Video 1.15 : Rust-built Python Tools Video 1.16 : Using Rust Ruff Linter Lesson 3: Python and Rust Command-Line Tools & Recap Video 1.17 : Using Polars with Python and Rust Video 1.18 : Polars CLI in Rust Video 1.19 : Polars CLI Test in Rust Video 1.20 : Polars-CLI Integration Test Video 1.21 : Polars Criterion Benchmarking Learning Objectives Understand the need for Rust and Python integration. Explore the PyO3 library and its usage. Understand the Rust ownership model and its usage in PyO3. Who Should Take This Course Python developers who want to learn Rust and its integration with Python. Rust developers who want to learn how to integrate Rust with Python. Developers who want to learn how to build command-line tools using Rust and Python.

Abstract: Achieving Scalability with Vector, Graph, and Key/Value Databases Description This week we explore vector and graph databases, powerful tools for managing and extracting insights from large, complex datasets. As data volumes continue to grow, scalability is crucial. We'll learn how vector and graph databases can efficiently store data while maintaining relationships, enabling more advanced analytics. Through real-world examples, you'll see how these databases unlock scalability for machine learning, fraud detection, social networks, and more. Learning Objectives Learn Vector, Graph, SQLand Key/Value Databases Learning to build solutions with Rust, Vector, Graph, and Key/Value Databases Learning advanced data engineering Additional Popular Resources 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Live Coding Rust Candle from Hugging Face Learning LLMOps This video series covers live coding Rust Candle from Hugging Face for LLMOps Lessons Covered Include: 1.0 Building binaries for Phi using AWS CodeBuild and Rust Candle Learning Objectives Run your own Rust LLMs Additional Popular Resources 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines

Abstract: With the accelerating speed of business and the increasing dependence on technology, companies today are significantly changing the way they build in-house business solutions. Many now use low-code and no code technologies to help them deal with specific issues, but that's just the beginning. With this practical guide, power users and developers will discover ways to resolve everyday challenges by building end-to-end solutions with the Microsoft Power Platform. Author Jason Rivera, who specializes in SharePoint and the Microsoft 365 solution architecture, provides a comprehensive overview of how to use the Power Platform to build end-to-end solutions that address tactical business needs. By learning key components of the platform, including Power Apps, Power Automate, and Power BI, you'll be able to build low-code and no code applications, automate repeatable business processes, and create interactive reports from available data. Learn how the Power Platform apps work together Incorporate AI into the Power Platform without extensive ML or AI knowledge Create end-to-end solutions to solve tactical business needs, including data collection, process automation, and reporting Build AI-based solutions using Power Virtual Agents and AI Builder

Abstract: Switch to Rust Switching to Rust from Python (Live Rough Draft Series) This video series covers how to switch to Rust from Python. It is in rough draft format and will be updated as the series progresses. The aim is to get this content out to the community as soon as possible. You can follow along with the code on GitHub at * Rust Tutorial- https://nogibjj.github.io/rust-tutorial/ . * Rust MLOps Template- https://github.com/noahgift/rust-mlops-template Lessons Covered Include: Lesson 1: Introduction to Leveling Up from Python to Rust The lesson is an introduction to a "Switch to Rust" course that covers the use of a live book of Rust lecture notes, installation and setup of Rust on AWS Cloud9, using GitHub Copilot for Rust development, and leveling up from Python to Rust. It also compares the energy efficiency of Python and Rust. 1.0 Introduction to Switch to Rust Course 1.1 Live Book of Rust Lecture Notes Overview 1.2 Rust Installation and Setup on AWS Cloud9 and explain why different than Python 1.3 Using GitHub Copilot to assist in Rust development and Leveling Up from Python. 1.4 Leveling up rust packaging actix microservice and crates 1.5 Energy efficiency of Python vs Rust Lesson 2: Building High Performance Rust Command Line Interfaces for MLOps, Distributed Systems, and Data Engineering This lesson describes the use of Rust for high performance Machine Learning Operations (MLOPs) with Hugging Face, including a comparison of systems programming in Rust and Python. It covers the creation of a high-performance data engineering tool in Rust that deduplicates data using Rayon for safe and memory efficient concurrency. The lesson also discusses building a high-performance GPU-accelerated Hugging Face Translator CLI using Rust. 2.0 High Performance MLOPs with Rust Hugging Face doing Zero Shot Classification 2.1 systems programming rust vs python for MLOPs 2.2 Building a high-performance data engineering tool with Rust that deduplicates data using Rayon with safe and memory efficient concurrency 2.3 Building a high-performance GPU-accelerated Hugging Face Translator CLI with Rust Lesson 3: Building GPU-accelerated MLOps with Rust In this lesson, we discuss the setup of reproducible GitHub Codespaces for GPU workflows using Stable Diffusion with Rust PyTorch bindings. Next we highlight the use of Amazon Firecracker in AWS Lambda as one of the most impressive use cases and go on to explain how to train models in Rust using PyTorch that target the GPU. The lesson also covers the creation of a CUDA-enabled stress test using Rust PyTorch bindings and Rayon for multithreaded GPU-accelerated MLOps 3.0 Reproducible GitHub Codespaces repo setup for GPU workflows with Stable Diffusion with Rust PyTorch bindings 3.1 In this video, I talk about one of the most impressive use cases, amazon #firecracker that powers #aws #lambda. Can you get bigger than this? Then I dive into training models in Rust with #pytorch that target the GPU. 3.2 Building a CUDA-enabled Stress Test with Rust PyTorch bindings and Rayon for multithreaded GPU-accelerated MLOps Lesson 4: Building Rust Containerized Solutions Lesson 5: Building Rust Cloud Computing Solutions for AWS 5.1 Building an Actix Web Server with Rust and Deploying to AWS App Runner Learning Objectives Learn program in Rust using Python as a reference and advanced tools like GitHub Copilot to assist Learning to build solutions with Rust including CLI, Web, and MLOps Learning to build Rust solutions for AWS, GCP, and Azure Learning to build Rust solutions for Kubernetes, Docker, and Serverless Learning to build Rust solutions for Data Engineering, Data Science, and Machine Learning Operations (MLOps) Learning to build Rust solutions for GPU-accelerated Machine Learning Learning the key syntax and features of the Rust Language Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Getting Started with the Zig Programming Language Learning the Language During Live Coding This video series covers the basics of the Zig programming language through live coding, allowing viewers to learn the language iteratively as it is being used. Lessons Covered 1.0 Getting Started Learning Objectives Learn the fundamentals of the Zig programming language Learn to build solutions with Zig Learn the key syntax and features of Zig Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Rust AWS Lambda Build and deploy serverless applications with Rust and AWS Lambda This course will help you build and deploy serverless applications with Rust and AWS Lambda. You will learn how to create, deploy, and manage AWS Lambda functions using Rust, leveraging the power and performance of the language for serverless architecture, and apply it by building a real-world Lambda function as a part of a distributed application. What you will learn Understand the concept of serverless architecture and AWS Lambda. Create and deploy AWS Lambda functions written in Rust. Integrate Lambda functions with other AWS services. Monitor, test, and optimize Rust-based Lambda functions. Implement real-world applications using Rust and AWS Lambda. Lesson 1: Getting Started with Rust AWS Lambda and Serverless Introduction to Serverless and AWS Lambda Walk through Rust Firecracker Project Setting up VSCode AWS Toolkit and CodeWhisperer for Rust Introduction to Cargo Lambda Rust Cost Advantage AWS Lambda Using the AWS Lambda Console Using the Step Functions Console Invoking Step Functions from AWS CLI Lesson 2: Advanced Techniques with Rust and AWS Lambda Building a Rust AWS Lambda Add Function Building a Rust AWS Lambda Divide by Two Function Invoking AWS Step Function from CLI Building Chainable AWS Step Functions with Rust Serverless MLOPs with EFS mounted in AWS Lambda Using Rust AWS Lambda Function URLs Saving money with arm64 Rust AWS Lambdas Lesson 3: Building a Polars Rust AWS Lambda Solution Polars Rust AWS Lambda Build and Deploy Polars Rust AWS Lambda Using AWS Console with deployed Polars Rust AWS Lambda Analyzing Rust AWS Lambda code with CodeWhisperer and AWS Toolkit AWS Lambda Function URLs Build and Deploy Polars Rust AWS Lambda Function URLs.

Abstract: AWS Certified Security - Specialty Exam Prep This video series provides comprehensive preparation for the AWS Certified Security - Specialty (SCS-C02) exam. Lessons Covered Include: Domain 1: Threat Detection and Incident Response 1.0 Introduction 1.1 Designing and Implementing Incident Response Plans 1.2 Detecting Security Threats and Anomalies with AWS Services 1.3 Responding to Compromised Resources and Workloads 1.4 Automating Incident Response with AWS Lambda 1.5 Conducting Root Cause Analysis with Amazon Detective 1.6 Capturing Forensics Data from Compromised Resources 1.7 Querying Logs to Validate Security Events 1.8 Preserving Forensic Artifacts with S3 Object Lock 1.9 Preparing and Recovering Services After Incidents 1.10 Incident Response Case Study 1.11 Practice Exam - Threat Detection and Response 1.12 Threat Detection and Incident Response Summary Learning Objectives Understand best practices for incident response in the cloud Explore AWS services to detect security threats Learn how to respond to compromised resources Domain 2: Security Logging and Monitoring 2.0 Introduction 2.1 Designing and Implementing Monitoring and Alerting 2.2 Troubleshooting Security Monitoring and Alerting 2.3 Designing and Implementing Logging Solutions 2.4 Troubleshooting Logging Solutions 2.5 Designing Log Analysis Solutions 2.6 Configuring AWS CloudTrail for Logging 2.7 Analyzing Logs with Amazon Athena 2.8 Monitoring Case Study 2.9 Practice Exam - Logging and Monitoring 2.10 Optimizing Log Storage Lifecycles 2.11 Third Party Log Analysis Tools 2.12 Security Logging and Monitoring Summary Learning Objectives Understand how to set up monitoring and alerts for security Learn best practices for logging and log analysis Gain skills in troubleshooting logging and monitoring Domain 3: Infrastructure Security 3.0 Introduction 3.1 Designing and Implementing Edge Service Security 3.2 Designing and Implementing Network Security 3.3 Designing and Securing Compute Workloads 3.4 Troubleshooting Network Security 3.5 Securing EC2 Instances with SSM 3.6 Scanning Images for Vulnerabilities 3.7 Infrastructure Security Case Study 3.8 Practice Exam - Infrastructure Security 3.9 Integrating AWS Firewall Manager 3.10 Applying Security Best Practices to Lambdas 3.11 Hardening AMIs with EC2 Image Builder 3.12 Infrastructure Security Summary Learning Objectives Learn how to secure AWS network infrastructure Understand options for compute and workload security Gain skills in troubleshooting infrastructure issues Domain 4: Identity and Access Management 4.0 Introduction 4.1 Designing Authentication for AWS Resources 4.2 Designing Authorization for AWS Resources 4.3 Troubleshooting with IAM Access Analyzer 4.4 Enforcing Least Privilege Access 4.5 Separating Duties with IAM Roles 4.6 Identity and Access Management Case Study 4.7 Practice Exam - Identity and Access Management 4.8 Securing Root User Credentials 4.9 IAM Policy Simulator for Troubleshooting 4.10 Enabling Federated Access with SSO 4.11 Managing Credentials and Secrets 4.12 Identity and Access Management Summary Learning Objectives Master IAM best practices for authentication and authorization Understand how to apply least privilege and separation of duties Learn to troubleshoot IAM issues Domain 5: Data Protection 5.0 Introduction 5.1 Data in Transit Confidentiality and Integrity 5.2 Data at Rest Confidentiality and Integrity 5.3 Managing Data at Rest Lifecycles 5.4 Protecting Credentials, Secrets, and Keys 5.5 Encrypting Data with AWS KMS 5.6 Data Protection Case Study 5.7 Practice Exam - Data Protection 5.8 Enforcing Data Retention with Glacier 5.9 Preventing Data Deletion with S3 Object Lock 5.10 Rotating RDS Credentials 5.11 Encrypting Data in Transit with SSL/TLS 5.12 Data Protection Summary Learning Objectives Learn techniques to protect data in transit and at rest Understand how to manage data lifecycles Gain skills in managing credentials and secrets Domain 6: Management and Security Governance 6.0 Introduction 6.1 Strategies for Central Account Deployment 6.2 Secure and Consistent Cloud Deployment 6.3 Evaluating Compliance of AWS Resources 6.4 Identifying Security Gaps through Reviews and Cost 6.5 AWS Organizations SCP Best Practices 6.6 Governance Case Study 6.7 Practice Exam - Governance 6.8 Automating Security Deployments 6.9 Tagging Resources for Governance 6.10 AWS Config for Security Assessments 6.11 AWS Well Architected Tool 6.12 Governance and Security Management Summary Learning Objectives Understand best practices for governing accounts and resources Learn how to align security with organizational requirements Gain skills in compliance, auditing, and deployment Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification AWS Solutions Architect Professional (SAP-C02) 2023 Assimilate Python From Zero.

Abstract: Rust for Pythonistas What you'll learn-and how you can apply it A multi-hour jam session where you will learn to code in Rust. * Write efficient and safe Rust code * Leverage Rust libraries and tools in your projects * Combine Rust with Python for improved application performance Additional Popular Resources 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: GitHub Foundations: Privacy, Security and Administration (Rough Draft) Updated (JIT) as it is built About This Video Course Building Secure and Efficient GitHub Workflows This video series covers live coding the GitHub Administration and Security domain iteratively, thus learning the best practices and nuances of managing and securing GitHub projects. Lessons Covered Include: 1.0 Course Introduction: Building Secure and Efficient GitHub Workflows 1.1 Introduction to Authentication and Security: Ensuring Your GitHub Account's Integrity 1.2 Securing Account with 2FA 1.3 Understanding Access Permissions 1.4 Enterprise Managed Users (EMUs) Explained 1.5 Introduction to GitHub Administration: Configuring and Managing Repositories and Organizations 1.6 Enabling and Disabling Features 1.7 Repository Permission Levels Explained 1.8 Setting Repository Visibility Options 1.9 Repository Privacy Settings and Options 2.0 Features and Options in the Security Tab 2.1 Understanding Repository Insights 2.2 Managing Collaborators in GitHub 2.3 Managing Organization Settings 2.4 Members, Teams, and Roles in a GitHub Organization 2.5 Next Steps: Continuing Your GitHub Mastery Journey Learning Objectives Learn GitHub's authentication and security measures Learning to build solutions with robust repository management Learning the key syntax and features of GitHub Administration and Security Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification AWS Solutions Architect Professional (SAP-C02) 2023 Assimilate Python From Zero.

Abstract: Negli ultimi dieci anni, con il ritorno delle reti neurali, la comprensione del Deep Learning è diventata essenziale e questo manuale fornisce un’introduzione approfondita per i data scientist e gli ingegneri del software con precedenti esperienze nel machine learning. Inizierete con le basi del Deep Learning e passerete rapidamente ai dettagli di importanti architetture avanzate, implementando tutto da zero. L’autore Seth Weidman vi mostra come funzionano le reti neurali usando un approccio basato su principi primi. Imparerete come applicare da zero le reti neurali multistrato, le reti neurali convoluzionali e quelle ricorrenti. Acquisendo una comprensione dettagliata di come queste reti funzionino matematicamente, computazionalmente e concettualmente, porterete a termine con successo i vostri futuri progetti di Deep Learning.

Abstract: Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory. Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field. Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and more Learn how to adapt mathematical methods to different applications from completely different fields Gain the mathematical fluency to interpret and explain how AI systems arrive at their decisions

Abstract: Go is an increasingly popular language for programming everything from web applications to distributed network services. This practical guide provides recipes to help you unravel common problems and perform useful tasks when working with Go. Each recipe includes self-contained code solutions that you can freely use, along with a discussion of how and why they work. Programmers new to Go can quickly ramp up their knowledge while accomplishing useful tasks, and experienced Go developers can save time by cutting and pasting proven code directly into their applications. Recipes include: Creating a module; Calling code from another module; Returning and handling an error; Converting strings to numbers (or converting numbers to strings); Modifying multiple characters in a string; Creating substrings from a string; Capturing string input; And so much more.--Back cover

Abstract: Computer security is a vast and complex field with many different technologies that must be combined correctly in an application. Learning all the security technologies can be challenging and confusing for application developers and architects. Adib Saikali provides a roadmap for application developers and architects to master application security. Adib identifies the security skills you should possess as an application developer and the key security protocols and technologies that every developer should know.

Abstract: Assimilate Google Machine Learning Certification Learn Google Machine Learning Certification This video course will show you how to learn Google Machine Learning Certification material to pass the exam. Topics Covered Include: 1.0 Introduction to OpenAI, a one hour exploration of many of the cutting edge AI models and projects you can build in the playground. 2.0 Assimilate Google Professional ML Certification EP2 problem framing heuristics and recommendation engines Learning Objectives Learn to master ML with the Google Machine Learning Certification course Learn to master ML with the Google Cloud Platform Additional Popular Resources 52 Weeks of AWS-The Complete Series Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: The best Linux administration course that prepares you for corporate jobs and for RHCSA, RHCE, LFCS, CLNP certifications About This Video Gain advanced Linux systems administration skills Understand Linux fundamentals and concepts Prepare for your Redhat Certified System Administrator (RHCSA - EX200) In Detail Linux is the number one operating system in the corporate world. It is a popular open-source operating system that is easy to use and highly secure. If you want to start your career in Linux and have little or no knowledge of Linux, then this course is for you. In this course, you will master Linux installation, configuration, administration, troubleshooting, the command line, OS tools, and much more. We have included resume and interview workshops that will help you get your dream IT job. This course will also help significantly in passing your RHCSA, RHCE, LFCS, and CompTIA Linux+ certification exams. By the end of this course, you will be a professional Linux administrator, be able to apply for Linux jobs and to take the EX-200 exam, and become a Redhat Certified System Administrator (RHCSA - EX200). Audience This course is designed for people who want to start a career in Linux, those who want to become a RedHat Certified System Administrator (RHCSA EX-200), and anyone keen to master Linux command-line skills.

Abstract: Learn to install Python from scratch with Github Codespaces. Also learn to use Github Copilot with Ludwig. 00:00 Intro 01:09 Create new Github Repository 01:58 Create new Github Codespace with 16 cores 02:62 Configure Visual Studio Code Dark Theme 03:47 apt-get update and apt-get install python development tools 04:32 Using htop to monitor multi-core load 05:13 downloading python from www.python.org 05:45 Installing python from source 06:40 ./configure --enable-optimizations 07:28 Compiling python with multi-core flag make -j 16 09:24 Finishing install with sudo make altinstall 10:07 Replacing system python by using the newly installed python with ~/.bashrc alias 11:07 Creating virtualenv and sourcing it inside of ~/.bashrc 12:22 Create project scaffold with requirements.txt and Makefile 12:00 Installing ludwig with make install command 13:53 Install Github Copilot 14:29 Commit code and setup Github Actions 17:41 Test out Github Copilot auto-complete with "ludwig".

Abstract: Learn what GIF animations are, why they are so popular, and how you can easily create your own for your website, email, or social media page using Photoshop and other Adobe apps. Author Jennifer Harder begins by providing a brief history of GIF animation before discussing its common uses on today's social media platforms, as well as its advantages and disadvantages. She'll then demonstrate how to prepare images using the Photoshop Timeline and Layers panels as they relate to GIF creation and how to transform graphics on each layer to create movement between frames. You'll also gain an understanding of the ideal Export settings for optimizing quality and file size for online use. Additionally, you'll see how to create GIF animations from short video clips and master the use of Illustrator to copy created stills for use in Photoshop. Finally, you'll explore other Adobe applications that can be used to create GIF animations as well as GIF alternatives for the Web. After completing this video, you will be able to create your own GIF animations for informational, promotional, or entertainment purposes. What You will Learn Understand GIF animation and its relevance in today's social media environment Optimize quality and file size for your GIF online Transform your graphics on each layer to create movement between frames Who Is This Video For Students, graphic artists, photographers, video artists/animators, and web designers with basic knowledge of Photoshop.

Abstract: Assimilate Databricks ML Certification Learn to pass Databricks ML Certification weekly by example This video course will show you how to understand the Databricks ML Certification exam and how to pass it. Topics Covered Include: 1.0 Getting started with Databricks and the ML Certification using Azure 2.0 Introduction to using Databricks clusters, the interface, notebooks and the Pandas API for Spark Learning Objectives Learn Databricks ML Certification material Learn Databricks clusters, notebooks and the Pandas API for Spark Additional Popular Resources 52 Weeks of AWS-The Complete Series Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Enterprise MLOps Interviews Learn Enterprise MLOps from the experts This video series interviews the experts at MLOps to learn how to use MLOps to build and deploy ML models. Interviews Include: Introduction GPT-3: O'Reilly authors Shubham Saboo and Sandra Kublik: I talk with the authors of the new O'Reilly book GPT-3 about a range of topics, including why they wrote the book. Conversation with Piero Molino and Ludwig/Predibase: Detailed conversation about Declarative AutoML with Piero Molino, author of Ludwig and co-founder Predibase. Asaf Somekh, CEO Iguazio: Talk at Duke MIDS MLOps Course: Life of a Model (or the brutal reality of applying ML in enterprises and how to deal with it). Javier Luraschi and Pedro Luraschi, Co-Founders of Hal9.ai: Discuss MLOps with Javascript, including no-code and low-code approaches and Tensorflow.js. Topics Covered Include: Enterprise MLOps MLOps MLOps on AWS MLOps on GCP MLOps on Azure MLOps and DevOps MLOps with Ludwig Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Why is the quantum computing market expected to grow by nearly $1.3 billion over the next five years? Given their quantum mechanical nature, quantum computers can solve difficult problems in fields such as chemistry, optimization, finance, and machine learning that classical computers find impossible to unravel. This pocket guide provides software developers with a quick reference to Qiskit, an open source SDK for working with quantum computers. Packed with helpful programming examples, tables, figures, and lists, this handy book helps you find the information you need to develop and debug quantum programs. Whether you're focused on business, engineering, or scientific applications, you'll learn how to choose and apply the appropriate Qiskit classes, methods, and functions. You'll also learn how to use the latest version of the Open Quantum Assembly Language, OpenQASM 3.0.

Abstract: TypeScript has conquered the world of JavaScript: it's one of the world's fastest growing and most popular languages across developer surveys, widely used in consumer and business companies alike, and frequently credited for helping massive web applications scale. But what is TypeScript? How does it work, why does it work, and how can we use it? Learning TypeScript takes beginner to intermediate JavaScript programmers from knowing nothing about "types" or a "type system" to full mastery of the fundamentals of TypeScript. It's more than a means to find bugs and typos--it's a useful system for declaring the way our JavaScript should work and helping us stick to it. You'll learn how TypeScript: interacts with JavaScript analyzes and understands code augments your existing development pattern helps you document your code works with IDEs to provide refactoring tools assists local development in refactoring code helps you develop more quickly with fewer bugs

Abstract: Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs

Abstract: Java developers usually tackle the complexity of software development through object-oriented programming (OOP). But not every problem is a good match for OOP. The functional programming (FP) paradigm offers you another approach to solving problems, and Java provides easy-to-grasp FP tools such as lambdas and streams. If you're interested in applying FP concepts to your Java code, this book is for you. Author Ben Weidig highlights different aspects of functional programming and shows you how to incorporate them in your code without going "fully functional." You'll learn how, when, and why to use FP concepts such as immutability and pure functions to write more concise, reasonable, and future-proof code. Many developers seek to expand their horizons by using OOP and FP together. It's no longer either-or; it's both. In two parts, this book includes: A Functional Approach: Get a high-level overview of functional programming, including the types already available to Java developers. Then explore different FP concepts and learn how to use them. Real-World Problems, Patterns, and Recipes: Apply what you've learned in part one to the typical real-world problems you might encounter in your daily work.

Abstract: Software engineers today typically put performance optimizations low on the list of development priorities. But despite significant technological advancements and lower-priced hardware, software efficiency still matters. With this book, Go programmers will learn how to approach performance topics for applications written in this open source language. How and when should you apply performance efficiency optimization without wasting your time? Authors Bartlomiej Plotka and Frederic Branczyk provide the tools and knowledge you need to make your system faster using fewer resources. Once you learn how to address performance in your Go applications, you'll be able to bring small but effective habits to your programming and development cycle. This book shows you how to: Continuously monitor for performance and efficiency regressions Find the root cause of performance bottlenecks using metrics, logging, tracing, and profiling Use tools like pprof, go test, benchstat and k6.io to create reliable micro- and macro-benchmarks Improve and optimize your code to meet your goals without sacrificing simplicity and readability Make data-driven decisions by prioritizing changes that make a difference Introduce basic "performance hygiene" in day-to-day Go programming and testing

Abstract: Whether you're new to Linux or have some experience, this practical book shows you how to master various tasks with this operating system--not just system administration. Cloud native professionals including developers, architects, DevOps practitioners, and site reliability engineers will learn how to use and program Linux in different modern environments, from embedded systems such as the Raspberry Pi to the virtual machine of your cloud provider of choice. Along the way, you'll gain hands-on experience with modern terminals, shells, and commands, use Linux networking, and learn how to manage your workloads, all with the goal of implementing modern Linux observability. You'll also understand how to run Linux applications in modern ways by using containers, systemd, modern filesystems, and immutable distros such as Flatcar and Bottlerocket. With this book, you will: Use Linux as a modern programming environment, not just as an admin tool Learn critical components such as the kernel, terminal multiplexer, human-friendly shells, and portable scripting Become familiar with access control, from file permissions to capabilities Understand the role of filesystems as a fundamental building block in Linux Gain hands-on experience with the Linux networking stack and tooling Learn how to apply modern operating system observability to manage your workloads Share data using SSH, rsync, and cloud sync mechanisms

Abstract: Do your product dashboards look funky? Are your quarterly reports stale? Is the dataset you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to any of the questions above, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck from the data reliability company Monte Carlo explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies. Build more trustworthy and reliable data pipelines Write scripts to make data checks and identify broken pipelines with data observability Program your own data quality monitors from scratch Develop and lead data quality initiatives at your company Generate a dashboard to highlight your company's key data assets Automate data lineage graphs across your data ecosystem Build anomaly detectors for your critical data assets

Abstract: Why is Google Analytics 4 the most modern data model available for digital marketing analytics? Because rather than simply report what has happened, GA4's new cloud integrations enable more data activation--linking online and offline data across all your streams to provide end-to-end marketing data. This practical book prepares you for the future of digital marketing by demonstrating how GA4 supports these additional cloud integrations. Author Mark Edmondson, Google Developer Expert for Google Analytics and Google Cloud, provides a concise yet comprehensive overview of GA4 and its cloud integrations. Data, business, and marketing analysts will learn major facets of GA4's powerful new analytics model, with topics including data architecture and strategy, and data ingestion, storage, and modeling. You'll explore common data activation use cases and get guidance on how to implement them. You'll learn: How Google Cloud integrates with GA4 The potential use cases that GA4 integrations can enable Skills and resources needed to create GA4 integrations How much GA4 data capture is necessary to enable use cases The process of designing dataflows from strategy though data storage, modeling, and activation

Abstract: This book is a complete guide to prepare for the CEH Certified Ethical Hacker certification exam. Leading experts Michael Gregg and Omar Santos help you master all the topics you need to know to succeed on your Certified Ethical Hacker Version 11 exam and advance your career in IT security. The authors concise, focused approach explains every exam objective from a real-world perspective, helping you quickly identify weaknesses and retain everything you need to know. Every feature of this book supports both efficient exam preparation and long-term mastery: Opening Topics Lists identify the topics you need to learn in each chapter and list EC-Councils official exam objectives Key Topics figures, tables, and lists call attention to the information that is most crucial for exam success Exam Preparation Tasks enable you to review key topics, define key terms, work through scenarios, and answer review questionsgoing beyond mere facts to master the concepts that are crucial to passing the exam and enhancing your career Key Terms are listed in each chapter and defined in a complete glossary, explaining essential terminology within the field This study guide helps you master all the topics on the latest CEH exam, including: Ethical hacking basics Technical foundations of hacking Footprinting and scanning Enumeration and system hacking Social engineering, malware threats, and vulnerability analysis Sniffers, session hijacking, and denial of service Web server hacking, web applications, and database attacks Wireless technologies, mobile security, and mobile attacks IDS, firewalls, and honeypots Cryptographic attacks and defenses Cloud computing, IoT, and botnets

Abstract: Three acknowledged experts in search engine optimization share guidelines and innovative techniques that will help you plan and execute a comprehensive SEO strategy. Complete with an array of effective tactics from basic to advanced, this fourth edition prepares digital marketers for 2022 and beyond with updates on SEO tools and new search engine optimization methods that have reshaped the SEO landscape. Novices will receive a thorough SEO education, while experienced SEO practitioners get an extensive reference to support ongoing engagements. Learn about the various intricacies and complexities of internet search Explore the underlying theory and inner workings of search engines and their algorithms Understand the interplay between social media engagement and other factors Discover tools to track results and measure success Examine the effects of key Google algorithm updates Consider opportunities for visibility in mobile, local, vertical, social, and voice search Build a competent SEO team with defined roles Gain insights into the future of search and internet discoverability

Abstract: Good software design is essential for the success of your project, but designing software is hard to do. You need to have a deep understanding of the consequences of design decisions and a good overview of available design alternatives. With this book, experienced C++ developers will get a thorough, practical, and unparalleled overview of software design with this modern language. C++ trainer and consultant Klaus Iglberger explains how you can manage dependencies and abstractions, improve changeability and extensibility of software entities, and apply and implement modern design patterns to help you take advantage of today's possibilities. Design is the most essential aspect of a software project because it impacts the software's most important properties: maintainability, changeability, and extensibility. Learn how to evaluate your code with respect to software design Understand what software design is, including design goals such as changeability and extensibility Explore the advantages and disadvantages of each design approach Learn how design patterns help solve problems and express intent Choose the right form of a design pattern to gain most of its advantages

Abstract: Object-Oriented Python (OOP) is a paradigm that combines data and code into cohesive units, allowing you to think differently about computational problems and solve them in a highly reusable way. Aimed at intermediate-level programmers, Object-Oriented Python is a hands-on tutorial that goes deep into the core tenets of OOP, showing you how to use encapsulation, polymorphism, and inheritance to write games and apps using Python. The book begins by demonstrating key problems inherent in procedural programming, then guides you through the basics of creating classes and objects in Python. You’ll build on this groundwork by developing buttons, text fields, and other GUI elements that are standard in event-driven environments. You’ll also use many real-world code examples and two pygame-based packages to help turn theory into practice, enabling you to easily write interactive games and applications complete with GUI widgets, animations, multiple scenes, and reusable game logic. In the final chapter, you’ll bring it all together by building a fully functional video game that incorporates many of the OOP techniques and GUI elements covered in the book. You’ll learn how to: •Create and manage multiple objects using an object manager object •Use encapsulation to hide the inner details of objects from client code •Use polymorphism to define one interface and implement it in multiple classes •Apply inheritance to build on existing code Object-Oriented Python is a visual, intuitive guide to fully understanding how OOP operates and how you can use it to make your code more maintainable, readable, and efficient—without sacrificing functionality.

Abstract: This is the first book to offer detailed guidance on how scenarios can be used to help organizations make their toughest decisions in a world of ever-escalating crisis and opportunity. To reap the full benefits of scenarios, you have to be able to apply them in the real world. This groundbreaking book goes beyond the theoretical to clearly explain different ways scenarios can be used in business decision-making—from strategic planning and financial modeling to crisis response. Connecting scenarios to strategy and action can have many benefits, including the ability to react quickly, anticipate major changes in the environment, and identify major opportunities. Thomas Chermack, a top expert on scenario planning, offers seven specific ways organizations can use scenarios and provides a wide variety of examples, along with proven processes, exercises, and workshops that have been used successfully in organizations across industries and countries for more than fifteen years.

Abstract: Growth is the goal. To help people develop their potential, to articulate and become the self that they want to be, are capable of being, and that best serves them and others in the short and long term is what we as individuals and leaders strive toward. But how do we grow? It turns out it happens in a predictable way, which means we can understand where we are in our growth and chart a way forward. In this compact, complete guide, Whitney Johnson helps you envision how growth happens and proactively direct yourself, or others in your organization, to help make the leaps needed to achieve goals. The growth and learning journey comes in three phases, the Launch Point, the Sweet Spot, and the High End, and within each phase, we play roles that keep us moving toward our goals. Compelling examples of successful people will show you when growth is slow and why, and how to keep going, and what to do when growth and learning are almost too fast to keep up with, and how to leap from one growth journey to another. As individuals grow so do organizations and societies. Growth is learning put into action, ideally action that betters the world as we better ourselves and our small niches within it, both personal and professional. Growth occurs when learning is internalized, when we try something new and invest the effort to move it from being something we do, to something we are.

Abstract: In this fourth edition of the bestselling business book Managing Humans , author Michael Lopp continues to draw leadership advice from some of the most important software companies of our modern age. Educational stories from companies across Silicon Valley such as Apple, Slack, Pinterest, Palantir, Netscape, and Borland detail the experiences of bright software engineers in an ever-changing industry This revised edition of Managing Humans expands on the previous editions’ explorations of management essentials including handling stress, building diverse teams, running inclusive meetings, and how to lead in times of crisis. The education of a great leader never stops, and Lopp applies crucial insights to help continue your never-ending leadership education. Whether it is approaching a myriad of engineering personalities or handling unexpected conflict, you will come away with wisdom to handle any team situation. The engineering culture of a company can determine the difference between a product’s ultimate success or failure. Managing Humans is here to guide managers and aspiring managers into the intimidating world of people and their vastly different personalities. Handle conflict, infuse innovation into your approach, and be the most confident manager you can be after reading this book. What You Will Learn Lead engineers Handle conflict Understand different engineering personalities Who This Book Is For Managers and would-be managers staring at the role of a manager wondering why they would ever leave the safe world of bits and bytes for the messy world of managing humans.

Abstract: When it comes to managing cybersecurity in an organization, most organizations tussle with basic foundational components. This practitioner’s guide lays down those foundational components, with real client examples and pitfalls to avoid. A plethora of cybersecurity management resources are available—many with sound advice, management approaches, and technical solutions—but few with one common theme that pulls together management and technology, with a focus on executive oversight. Author Ryan Leirvik helps solve these common problems by providing a clear, easy-to-understand, and easy-to-deploy foundational cyber risk management approach applicable to your entire organization. The book provides tools and methods in a straight-forward practical manner to guide the management of your cybersecurity program and helps practitioners pull cyber from a “technical” problem to a “business risk management” problem, equipping you with a simple approach to understand, manage, and measure cyber risk for your enterprise. What You Will Learn Educate the executives/board on what you are doing to reduce risk Communicate the value of cybersecurity programs and investments through insightful risk-informative metrics Know your key performance indicators (KPIs), key risk indicators (KRIs), and/or objectives and key results Prioritize appropriate resources through identifying program-related gaps Lay down the foundational components of a program based on real examples, including pitfalls to avoid Who This Book Is For CISOs, CROs, CIOs, directors of risk management, and anyone struggling to pull together frameworks or basic metrics to quantify uncertainty and address risk

Abstract: The next-generation IBM® c-type Directors and switches for IBM Storage Networking provides high-speed Fibre Channel (FC) and IBM Fibre Connection (IBM FICON®) connectivity from the IBM Z® platform to the storage area network (SAN) core. It enables enterprises to rapidly deploy high-density virtualized servers with the dual benefit of higher bandwidth and consolidation. This IBM Redpaper Redbooks publication helps administrators understand how to implement or migrate to an IBM c-type SAN environment. It provides an overview of the key hardware and software products, and it explains how to install, configure, monitor, tune, and troubleshoot your SAN environment.

Abstract: Build secure and reliable IoT applications for micro:bit and Raspberry Pi Pico by using Rust and Tock. One of the first Operating Systems written in Rust, Tock is designed to safely run multiple applications on low power devices, enabling you to build a secure foundation for IoT systems. It is an open-source OS that has recently gained popularity as companies such as Google[1] explore and integrate it into their products. This book guides you through the steps necessary to customize and integrate Tock into your devices. First, you'll explore the characteristics of Tock and how to run it on two of the most popular IoT platforms: micro:bit and Raspberry Pi Pico. You’ll also take a look at Rust and how to use it for building secure applications with Tock. The book focuses on the Tock kernel internals and presents the steps necessary to integrate new features. From simple drivers to the more complex asynchronous ones, you are provided with a detailed description of the Tock kernel API. Next, you'll review the Tock applications framework for C. Starting from simple Tock APIs to the more complex Inter-Process Communication system, this book provides a complete overview of the Tock application ecosystem. By taking a practical approach, Getting Started with Secure Embedded Systems provides a starting point for building a secure IoT foundation using the Tock Operating System. You will: Use Rust for embedded systems development Write applications and drivers for Tock Customize the Tock kernel for specific hardware platforms Set a solid base for building secure and reliable IoT applications Use Tock to ensure the security of your microcontrollers and integrate them into your projects Manage products that rely on Tock Who This Book Is For IoT system designers, developers, and integrators who are familiar with operating systems concepts. The book can also be suitable for people with less experience, who want to gain an overview of the latest hardware and software technologies related to building secure IoT systems.

Abstract: This IBM® Redpaper® publication describes best practices for deploying and using advanced Broadcom Fabric Operating System (FOS) features to identify, monitor, and protect Fibre Channel (FC) SANs from problematic devices and media behavior. Note that this paper primarily focuses on the FOS command options and features that are available since version 8.2 with some coverage of new features that were introduced in 9.0. This paper covers the following recent changes: SANnav Fabric Performance Impact Notification

Abstract: Developing Classification and Regression Systems (Machine Learning with Python for Everyone Series), Part 3 Sneak Peek The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing. Dr. Mark Fenner, owner of Fenner Training and Consulting, LLC, has taught computing and mathematics to diverse adult audiences since 1999, and holds a PhD in computer science. His research has included design, implementation, and performance of machine learning and numerical algorithms; developing learning systems to detect user anomalies; and probabilistic modeling of protein function.

Abstract: A practical guide for software architects and Java developers to build cloud-native hexagonal applications using Java and Quarkus to create systems that are easier to refactor, scale, and maintain Key Features Learn techniques to decouple business and technology code in an application Apply hexagonal architecture principles to produce more organized, coherent, and maintainable software Minimize technical debts and tackle complexities derived from multiple teams dealing with the same code base Book Description Hexagonal architecture enhances developers' productivity by decoupling business code from technology code, making the software more change-tolerant, and allowing it to evolve and incorporate new technologies without the need for significant refactoring. By adhering to hexagonal principles, you can structure your software in a way that reduces the effort required to understand and maintain the code. This book starts with an in-depth analysis of hexagonal architecture's building blocks, such as entities, use cases, ports, and adapters. You'll learn how to assemble business code in the Domain hexagon, create features by using ports and use cases in the Application hexagon, and make your software compatible with different technologies by employing adapters in the Framework hexagon. Moving on, you'll get your hands dirty developing a system based on a real-world scenario applying all the hexagonal architecture's building blocks. By creating a hexagonal system, you'll also understand how you can use Java modules to reinforce dependency inversion and ensure the isolation of each hexagon in the architecture. Finally, you'll get to grips with using Quarkus to turn your hexagonal application into a cloud-native system. By the end of this hexagonal architecture book, you'll be able to bring order and sanity to the development of complex and long-lasting applications. What you will learn Find out how to assemble business rules algorithms using the specification design pattern Combine domain-driven design techniques with hexagonal principles to create powerful domain models Employ adapters to make the system support different protocols such as REST, gRPC, and WebSocket Create a module and package structure based on hexagonal principles Use Java modules to enforce dependency inversion and ensure isolation between software components Implement Quarkus DI to manage the life cycle of input and output ports Who this book is for This book is for software ar...

Abstract: CEH v11 Certified Ethical Hacker Exam Cram is the perfect study guide to help you score higher on the updated EC-Council CEH v11 exam. Using the proven Exam Cram method of study, it offers comprehensive foundational learning for all facets of ethical hacking and penetration testing. Chuck Easttoms expert real-world approach reflects both his expertise as one of the leading cybersecurity practitioners and instructors in the world, as well as test-taking insights he has gained from teaching CEH preparation courses worldwide, including courses taught directly for EC-Council. Easttom assumes no prior knowledge: readers will little or no experience in ethical hacking and penetration testing can obtain the knowledge they need to take and pass the exam. He thoroughly covers every CEH v11 topic, including: Reconnaissance and scanning Enumeration and vulnerability scanning System and session hacking Malware, sniffing, social engineering, and DOS attacks Evading security measures Hacking web servers, applications, wireless, mobile, IoT, and OT Cloud computing, cryptography, and more Extensive preparation tools include topic overviews, exam alerts, CramSavers, CramQuizzes, chapter-ending review questions, author notes and tips, and an extensive glossary. The handy Cram Sheet tear-out brings together tips, acronyms, and memory joggers not available anywhere else -- perfect for last-minute study. Powerful Pearson Test Prep practice test software offers an extensive collection of exam-realistic practice questions, with many customization and reporting features: test yourself in study mode, practice exam mode, or flash card mode. The companion website also provides access to several digital assets including the Glossary and Cram Sheet.

Abstract: Learn the fundamentals of Godot by diving headfirst into creating a 2D platformer from scratch. This book is a hands-on, practical guide to developing 2D games using the Godot Engine 3.2.3/3.3, with the help of GDScript. Author Maithili Dhule begins by explaining some basic tools and techniques used to make games, the factors that need to be considered while choosing a game engine, and pointing out the benefits of using Godot. She then walks you through downloading the engine and guides you as you explore key features of its interface. Next, you’ll receive a concise introduction to the basics of GDScript, the main scripting language used in Godot, before moving on to essential topics such as Godot’s node-scene architecture, the interaction of various physics bodies, the creation of game scenes, and writing scripts. As the book progresses, you’ll learn how to create and animate your game character, design the game world, add enemies, and implement a coin-collection system. You’ll also see how the user’s gaming experience can be enhanced through the addition of parallax backgrounds, a title screen, music, and sound effects. Toward the end of the book, you’ll learn how to export your game to different platforms, both mobile and PC, as well as possible avenues for monetizing the game. Throughout the book, theoretical concepts are supplemented with concrete, ready-to-implement examples that you can try out. Upon finishing this book, you’ll be able to make and publish your first 2D platform game. Beginning Game Development with Godot is for game development enthusiasts of all levels interested in creating their own games. What You Will Learn Understand the Godot engine and the benefits of using it for game development Master the fundamentals of programming in GDScript Use the Godot graphical interface to design and animate players, the game world, menus, and various games scenes Create your first 2D game in Godot and publish it to various platforms Who This Book Is For Aspiring game developers who may be new to game development, as well as experts exploring the potential of the Godot Engine.

Abstract: Take a holistic view of enterprise risk-adjusted return management in banking. This book recommends that a bank transform its siloed operating model into an agile enterprise model. It offers an event-driven, process-based, data-centric approach to help banks plan and implement an enterprise risk-adjusted return model (ERRM), keeping the focus on business events, processes, and a loosely coupled enterprise service architecture. Most banks suffer from a lack of good quality data for risk-adjusted return management. This book provides an enterprise data management methodology that improves data quality by defining and using data ontology and taxonomy. It extends the data narrative with an explanation of the characteristics of risk data, the usage of machine learning, and provides an enterprise knowledge management methodology for risk-return optimization. The book provides numerous examples for process automation, data analytics, event management, knowledge management, and improvements to risk quantification. The book provides guidance on the underlying knowledge areas of banking, enterprise risk management, enterprise architecture, technology, event management, processes, and data science. The first part of the book explains the current state of banking architecture and its limitations. After defining a target model, it explains an approach to determine the "gap" and the second part of the book guides banks on how to implement the enterprise risk-adjusted return model. What You Will Learn Know what causes siloed architecture, and its impact Implement an enterprise risk-adjusted return model (ERRM) Choose enterprise architecture and technology Define a reference enterprise architecture Understand enterprise data management methodology Define and use an enterprise data ontology and taxonomy Create a multi-dimensional enterprise risk data model Understand the relevance of event-driven architecture from business generation and risk management perspectives Implement advanced analytics and knowledge management capabilities Who This Book Is For The global banking community, including: senior management of a bank, such as the Chief Risk Officer, Head of Treasury/Corporate Banking/Retail Banking, Chief Data Officer, and Chief Technology Officer. It is also relevant for banking software vendors, banking consultants, auditors, risk management consultants, banking supervisors, and government finance professionals.

Abstract: Get to grips with React Hooks and design your own custom Hook to manage application states for making better decisions in site architecture Key Features Get to grips with Hooks' design and understand each built-in Hook's pitfalls with examples Discover how to turn your existing code into a reusable Hook via code refactoring Explore design solutions to identify and solve site performance issues involving Hooks Book Description React hook creates a unique solution for using states in function components to orchestrate UI communication. They provide you with an easy interface to write custom data management solutions with low development and maintenance costs. Understanding how Hooks are designed enables you to use them more effectively, and this book helps you to do just that. This book starts with a custom-crafted solution to reveal why Hooks are needed in the first place. You will learn about the React engine and discover how each built-in Hook can manage a persistent value by hooking into it. You will walk through the design and implementation of each hook with code so that you gain a solid understanding. Finally, you'll get to grips with each Hook's pitfalls and find out how to effectively overcome them. By the end of this React book, you'll have gained the confidence to build and write Hooks for developing functional and efficient web applications at scale. What you will learn Create your own hooks to suit your state management requirement Detect the current window size of your website using useEffect Debounce an action to improve user interface (UI) performance using useMemo Establish a global site configuration using useContext Avoid hard-to-find application memory leaks using useRef Design a simple and effective API data layer using custom Hooks Who this book is for This book is for web developers who are looking for a consistent and efficient approach for applying application states with Hooks. Basic knowledge of React will help you to get the most out of this book.

Abstract: Learn the Apple Swift Languages by using the XCode Playground environment.

Abstract: The cloud is becoming the de facto home for companies ranging from enterprises to startups. Moving to the cloud means moving your applications from monolith to microservices. But once you do, maintaining and running these services brings its own level of complexity. The answer? Modularity, deployability, observability, and self-healing capacity through cloud native development. With this practical book, Nishant Singh and Michael Kehoe show you how to build a true cloud native infrastructure on Microsoft Azure, following guidelines from the Cloud Native Computing Foundation (CNCF). DevOps and site reliability engineers will learn how adapting applications to cloud native early in the design phase helps you fully utilize the elasticity and distributed nature of the cloud. Chapters include: "Introduction: Why Cloud Native?" "Infrastructure as Code: Setting Up the Gateway" "Containerizing Your Application: More Than Boxes" "Kubernetes: The Grand Orchestrator" "Creating a Kubernetes Cluster on Azure" "Observability: Following the Breadcrumbs" "Service Discovery and Service Mesh: Finding New Territories and Crossing Borders" "Networking and Policy Management: Behold the Gatekeepers" "Distributed Databases and Storage: The Central Bank" "Getting the Message" "Serverless"

Abstract: Causal inference lies at the heart of our ability to understand why things happen by helping us predict the results of our actions. This process is vital for businesses that aspire to turn data and information into valuable knowledge. With this report, data scientists and analysts will learn a principled way of thinking about causality, using a suite of causal inference techniques now available. Authors Hugo Bowne-Anderson, a data science consultant, and Mike Loukides, vice president of content strategy at O'Reilly Media, introduce causality and discuss randomized control trials (RCTs), key aspects of causal graph theory, and much-needed techniques from econometrics. You'll explore: Techniques from econometrics, including randomized control trials, the causality gold standard used in A/B-testing The constant-effects model for dealing with all things not being equal across the groups you're comparing Regression for dealing with confounding variables and selection bias Instrumental variables to estimate causal relationships in situations where regression won't work Techniques from causal graph theory including forks and colliders, the graphical tools for representing common causal patterns Backdoor and front-door adjustments for making causal inferences in the presence of confounders

Abstract: The dramatic increase in minority- and female-owned companies continues to transform the business world while setting standards for those who follow. Thriving as a Minority-Owned Business in Corporate America offers you a comprehensive guide to current practical knowledge of minority business development, from grants and loans to market building. This book demonstrates how you can use specific laws, institutions, and new technologies to set up and steer your business to success. Expert coverage includes both established and underused resources at the federal, state, and local levels dedicated to minority business expansion. You will learn how to tap resources made available by government agencies like the Minority Business Development Agency (MBDA) and programs such as the Offices of Minority and Women Inclusion (OMWI). Non-governmental funding sources (e.g., banks, credit unions, venture capital) are also examined in depth, with sound advice on approaching each. The author explores the critical role of social media in leveling the playing field, spotlighting minority/female business-related sites and strategies for leveraging your online presence. And he provides real-world guidance on business certifications, tax breaks, credit issues, and more. Whether you’re in start-up or expansion mode, after reading this book, you will have the know-how needed to seize the opportunity and succeed with your enterprise. What You Will Learn Discover unused and unrecognized resources at the federal, state, and local level set up specifically for minority business See the difference between banks, thrifts, credit unions, angel investors, and venture capital, and how to approach each Use social media in support of minority business development goals Examine social media sites and trends: current and relevant minority business related social media sites and trends Who This Book is For Anyone: Asian, Hispanic, women, Black or White who wants authentic, impactful information on creating or supporting minority-owned businesses.

Abstract: Get to grips with the tools, services, and functions needed for application migration to help you move from legacy applications to cloud-native on Google Cloud Key Features Discover how a sample legacy application can be transformed into a cloud-native application on Google Cloud Learn where to start and how to apply application modernization techniques and tooling Work with real-world use cases and instructions to modernize an application on Google Cloud Book Description Legacy applications, which comprise 75–80% of all enterprise applications, often end up being stuck in data centers. Modernizing these applications to make them cloud-native enables them to scale in a cloud environment without taking months or years to start seeing the benefits. This book will help software developers and solutions architects to modernize their applications on Google Cloud and transform them into cloud-native applications. This book helps you to build on your existing knowledge of enterprise application development and takes you on a journey through the six Rs: rehosting, replatforming, rearchitecting, repurchasing, retiring, and retaining. You'll learn how to modernize a legacy enterprise application on Google Cloud and build on existing assets and skills effectively. Taking an iterative and incremental approach to modernization, the book introduces the main services in Google Cloud in an easy-to-understand way that can be applied immediately to an application. By the end of this Google Cloud book, you'll have learned how to modernize a legacy enterprise application by exploring various interim architectures and tooling to develop a cloud-native microservices-based application. What you will learn Discover the principles and best practices for building cloud-native applications Study the six Rs of migration strategy and learn when to choose which strategy Rehost a legacy enterprise application on Google Compute Engine Replatform an application to use Google Load Balancer and Google Cloud SQL Refactor into a single-page application (SPA) supported by REST services Replatform an application to use Google Identity Platform and Firebase Authentication Refactor to microservices using the strangler pattern Automate the deployment process using a CI/CD pipeline with Google Cloud Build Who this book is for This book is for software developers and solutions architects looking to gain experience in modernizing their enterprise applications to run on Google Cloud and t...

Abstract: Stay updated and level up your skills with the new .NET 6 features, C# 10 features, Hot Reload, .NET Upgrade Assistant, NET Interactive Assistant, and more About This Video Keep yourself updated with new features introduced in .NET 6 and C# 10 Each lesson in this course is bite-sized and easy to finish Practice activities are shared to improve code-writing skills with new features In Detail .NET is one of the most popular frameworks used to develop web, desktop, and mobile applications. The usage of C# has dramatically increased in recent times for productive development. Companies such as StackOverflow, UPS, GE Aviation, and Siemens use .NET as the framework for their software development. In this course, you will get familiarized with the new features introduced in .NET 6 and C# 10. We will cover topics such as What’s New in .NET 6, What’s New in C# 10, Hot Reload, .NET Upgrade Assistant, .NET Interactive Assistant, and some more advanced features in .NET 6. This course provides 2 hours of content along with practice activities. To help you better, it follows a step-by-step approach for learning new features introduced in .NET 6 and C# 10. By the end of this course, you will be aware of the new features introduced in .NET 6 and C# 10 and will be ready to apply the new features in your existing or new projects. Who this book is for This course will be beneficial for developers who use C# as their primary programming language, and architects who want to keep updated on the latest happenings in the development community. You should know C# basics to understand the new concepts covered in the course and Visual Studio Code or Visual Studio to try out the new concepts you learn from this course.

Abstract: Leadership is a set of abilities with which a lucky few are born. They're the natural relationship builders, master negotiators and persuaders, and agile and strategic thinkers. The good news for the rest of us is that those abilities can be developed. In The Leader's Brain: Enhance Your Leadership, Build Stronger Teams, Make Better Decisions, and Inspire Greater Innovation with Neuroscience, Wharton Neuroscience Initiative director Michael Platt explains how. Over two decades as a professor and practitioner in neuroscience, psychology, and marketing, Platt's pioneering research has deepened our understanding of how key areas of the brain work-and how that understanding can be applied in business settings. In The Leader's Brain, Platt explains: why two managers, when presented with the same set of information, make very different decisions; why some companies (Apple) build strong social and emotional connections with their customers and others do not (Samsung); how some of the most significant events in sports history, like the "Miracle on Ice," contain insights for how to build a team; and why even some of the most visionary business leaders can make disastrous decisions, and how to fix that. The Leader's Brain relates findings like these, and many more, to help enhance leadership in an ever-shifting world entering a "new normal."

Abstract: Discover what sets leaders like President Biden apart from the rest In The Joe Biden Way: How to Become a Bold and Empathic Leader, bestselling author and leadership expert Jeffrey Krames provides listeners with leadership secrets gleaned from one of the most transformative and successful presidents in modern times: Joseph Robinette Biden, Jr. In this book, the author sets out seven lessons in inspiring leadership that have helped the forty-sixth president of the United States carry his powerful message to the White House and deliver it to hundreds of millions of people. You'll learn how to: lead with empathy and demonstrate you understand what your followers are experiencing; set a single priority and focus on it with laser precision; learn to execute on your goals and back your words with meaningful action; build on and cultivate your strengths and values; and lead diverse groups of people and inspire them to share a common goal. Perfect for executives, managers, and other business leaders, The Joe Biden Way is a must-have resource for anyone who strives to unlock the best in their followers and colleagues and discover what sets great leaders apart from the rest of the pack.

Abstract: In today's world, leadership is all about establishing community and connectivity so everyone can be part of something bigger than themselves. To have the grace to create this kind of leadership, we need greater self-awareness and genuine connection to others. In The Five Graces of Life and Leadership, CEO of the celebrated consulting firm Korn Ferry delivers a meaningful and thought-provoking exploration of leadership, emphasizing the five kinds of grace that leaders must have to lead their teams in today's evolving workscape. In the book, you'll learn how to the best leaders make their teams feel comforted, safe, and secure that they're headed in the right direction. It includes insightful discussions on each of the five indispensable graces, including: Gratitude-the attitude that elevates our spirits, boosts morale, and lifts our hearts; Resilience-the quality that allows us to achieve beyond our wildest dreams; Aspiration-the knowledge that we can make tomorrow better than today; Courage-the ability to understand and move beyond our fears; and Empathy-the understanding needed to connect with others from their perspectives. The perfect book for managers, executives, and other business leaders, The Five Graces of Life and Leadership is a can't miss book on the human side of leadership at work, at home, and anywhere else.

Abstract: Gain the knowledge you need to start your study towards the Java SE 11 developer exam (1Z0-819). The Java SE 11 developer exam (1Z0-819) was released in September 2020 and effectively combines the preview Programmer I and II exams. There is currently limited material specifically designed to address this new exam. Material that does exist is split across two resources and does not address directly the new certification. The modules present a subset of those essential core topics that anyone who wants to learn Java must know. Regardless of whether or not they wish to take the certificate, each module can be viewed in isolation thereby providing a flexible resource for anyone wanting to ramp up on these topics. It covers sufficient knowledge to allow the candidate to develop non-trivial Java applications. What You Will Learn What are the core concepts and essential Java data types How to work with operators, execution, exceptions, methods, class design and more How to work with the collections framework and its some methods How to use variables and scopes to store and reference data How to loop and branch code and make runtime decisions How to handled errors and exceptions correctly How to design classes using interfaces, abstract classes and encapsulation Who This Video Is For Java developers that want to formalize their current knowledge by obtaining an official Oracle certificate; recent computer science graduates who what to distinguish themselves from the crowd and specialize in Java development with a highly sort after certificate; already certified Java developers who want to upgrade their knowledge of Java; Java developers who want to take the upgrade exam (1Z0-817 – those with OCP Java 6/7/8); and junior developers who just want to learn about a specific topic covered by one or more of the modules.

Abstract: Take the anxiety out of tax season and file your return with confidence In Taxes For Dummies, 2022 Edition, you'll get line-by-line advice and plan ahead strategies that take the fear and anxiety out of tax season and save you money now and in the months and years ahead. This completely updated edition includes detailed coverage of the numerous tax bills have passed in recent years. You'll learn everything you need to know to file your own taxes with confidence and intelligently plan year-round tax strategies. In this book, you'll: Discover how to take advantage of every deduction and tax credit that applies to your specific circumstances Learn to navigate the IRS website and the newest versions of the most popular online tax preparation and filing options Understand new retirement account options and the implications of new foreign taxation rules Plan ongoing, multi-year tax strategies that will help you achieve your financial goals at every stage of your life Taxes For Dummies, 2022 Edition is the perfect resource for any United States taxpayer planning to file their own 2021 taxes. Whether you're a first-time taxpayer, an expat filing from outside the US, or a seasoned veteran of tax season looking for the latest deductions and strategies to reduce your tax bill, this book is a must-read resource that'll transform how you think about taxes.

Abstract: Make the best of your test suites by using cutting-edge software architecture patterns in Python Key Features Learn how to create scalable and maintainable applications Build a web system for micro messaging using concepts in the book Use profiling to find bottlenecks and improve the speed of the system Book Description Developing large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier. This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites. Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished. By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems. What you will learn Think like an architect, analyzing software architecture patterns Explore API design, data storage, and data representation methods Investigate the nuances of common architectural structures Utilize and interoperate elements of patterns such as microservices Implement test-driven development to perform quality code testing Recognize chunks of code that can be restructured as packages Maintain backward compatibility and deploy iterative changes Who this book is for This book will help software developers and architects understand the structure of large complex systems and adopt architectural patterns that are scalable. Examples in the book are implemented in Python so a fair grasp of basic Python concepts is ex...

Abstract: With .NET 5s ML.NET and Programming ML.NET , any Microsoft .NET developer can solve serious machine learning problems, increasing their value and competitiveness in some of todays fastest-growing areas of software development. World-renowned Microsoft development expert Dino Esposito covers everything you need to know about ML.NET, the machine learning pipeline, and real-world machine learning solutions development. Modeled on his popular Programming ASP.NET books, this guide takes the same scenario-based approach Microsofts team used to build the ML.NET framework itself. Esposito presents and illuminates ML.NETs dedicated mini-frameworks (ML Tasks) for specific classes of problems, and draws on personal experience to help developers apply these in the real world, where a problems complexity can vary widely based on data availability or the specific results you need. In a full section on ML.NET neural networks, Esposito introduces key concepts and presents realistic examples you can reuse in your own applications. Along the way, Esposito also shows how to leverage powerful Python-based machine learning tools in the .NET environment. Programming ML.NET will help you add machine learning and artificial intelligence to your tool belt, whether you have a background in these high-demand technologies or not.

Abstract: After setting up your development environment in Creating a Spring Boot REST API with iPad Pro and Raspberry Pi 4, continue learning to build a complex and practical web application anywhere with a minimalistic setup. Not only will you get to experience technologies used in famous enterprise web applications, you will also be able to code using only your iPad and a Raspberry Pi. The common misconception is that you can only use your iPad for small code changes, or small code additions while on the go. You will learn that you can do so much more and code an entire application with just your iPad and Raspberry Pi. In this second video, secure the REST API from the previous tutorial using Spring Security. Given that the test application you created will handle personal finances, securing the API is a mandatory step in the development of your project. Also, it’s fascinating to be able to create a secure API using only an iPad and a Raspberry Pi. What You'll Learn Support authentication on the the device and server Learn about the Security Payload Take full stack development to another, mobile level Who This Video Is For Tech enthusiasts who want to use only an iPad and a Raspberry Pi to build complex web applications on the go. Developers eager to learn how to architect and code full stack applications with minimalist tech.