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: In DevOps, SRE, and operations, toil is the enemy. Fortunately, the repetitive and time-consuming manual work that drains team resources is steadily being automated. As a result, the automation tooling landscape has expanded to encompass a wide range of tasks. Whether it's testing, infrastructure configuration and management, provisioning, monitoring, or observability, there's now a tool to automate it. Evaluating and choosing among these tools is critical to the success of DevOps and SRE. Join us for in-depth sessions with leading experts to explore what it means to automate, what successful automation looks like, and how to assess the available tools and determine the right ones for your needs. What you'll learn and how you can apply it Understand how to tame your infrastructure as code using architectural patterns for infrastructure as code architecture Learn the basics of working with Terraform in production environments Explore the integration of Crossplane and Kyverno to automate cluster creation, resource configuration, compliance enforcement, add-on deployment, and security checks This live course is for you because... You're a DevOps engineer or SRE for whom understanding and implementing automation is part of the job. You're a platform engineer tasked with evaluating and implementing an automation toolchain that drives developer efficiency by reducing toil. You're a sysadmin or an operations engineer who wants to learn a more efficient, nonmanual way to build, control, and modify your infrastructure. Recommended follow-up: Read Infrastructure as Code, second edition (book) Read Terraform: Up and Running, third edition (book) Read Infrastructure as Code: Patterns and Practices (book) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

Abstract: This is the one stop shop for all What's New in Software Development interviews of 2024 in their audio format. Keep up-to-date with Sam Newman and his colleagues on their software development journeys.

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: Observability is more difficult in the era of large language models, while insight into your code's behavior is increasingly more important. Join Sam Newman and Jessica Kerr for a discussion about the impact of AI on software production. They explore what happens when deterministic work (software development) meets nondeterministic work (GenAI) and examine some of the limitations of communicating with an AI at scale. This event is for anyone who builds or maintains software and is looking to better understand the intersection of GenAI and observability. What's New in Software Development gives you a chance to explore trending topics in software development and to hear from Sam and Jessica Kerr about software development, how to begin implementing AI tooling into your own work, and their own career journeys. They will spend a few minutes covering the trends that are influencing software development and then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it How to start thinking about integrating GenAI into your production lifecycle How to use observability to gain insight into how your code behaves in production This live course is for you because... You want to hear from Sam Newman and Jessica Kerr about how software development is changing. Recommended Follow-Up: Read Observability Engineering (book).

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: Software development is increasingly central to a business’s identity. But as the complexity of the practice grows, the demand is high for developers who operate at a senior level. And the rise in generative AI tools means that even expert developers must recalibrate how they work to keep up with the pace of development. Join us to level up your skills and accelerate your journey to senior software engineer. These in-depth sessions cover some of the biggest challenges facing software developers today, teaching you practical methods and best practices to improve coding and software design, better manage data, mentor new engineers, and collaborate with your team.

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: 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: Join Sam Newman and Evan Bottcher for a discussion about the evolution of internal developer platforms and how to design teams that support a cohesive architecture reflected in underlying systems, features, processes, data, and APIs. Team arrangement, or topology, leads to "forces of alignment," which helps in making better technology decisions for both developers and external customers. What you'll learn and how you can apply it Explore how to make tool choices and organize workflows to optimize developer productivity Learn what constitutes an effective platform engineering team Understand the core values and objectives of successful platform engineering This live course is for you because... You want the chance to hear from Sam Newman and Evan Bottcher about how infrastructure & ops is changing. Recommended follow-up: Read Platform Engineering on Kubernetes (book) Watch Infrastructure & Ops Hour: Platform Engineering with Camille Fournier (video).

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: Join us for a special conversation with Sam Newman and Datasette creator Simon Willison, who'll discuss using large language models to support self-guided learning of new programming languages and other skills. A language model such as GPT-3 can act as a sort of super-smart-and-super-dumb teaching assistant: you can ask it questions and follow-up questions, and if you get your questions right, it can genuinely help you build a good mental model of the topic at hand. You'll also hear about some of the ways that Simon is able to maintain 185 different open source projects at the same time. What you'll learn and how you can apply it Learn what really matters for software design Find out what's coming next for software development This recording of a live event is for you because... You want the chance to hear from Sam Newman and Simon Willison about software development. You need help tackling a new programming language or other skill. Recommended follow-up: Read Fluent Python, second edition (book) Explore O'Reilly's Django Sandbox Watch Software Development Superstream: Becoming a Senior Software Engineer (live event video).

Abstract: Climate disaster is looming, and the day of reckoning is here. Businesses can no longer afford to ignore their part in the changing climate. Environmental sustainability is now a top strategic priority for IT teams, and for good reason. Greener computing practices are not only good for the planet but can also be a driver of cost-efficiency and innovation. The leading cloud providers have all pledged to decarbonize their data centers and use renewable energy, but how can organizations and individual contributors take part and hold them accountable? What are the impacts of your cloud use? And how can your organization be more efficient? Join leading experts for a half-day of sessions that will answer these tough questions and set you on the path to greener cloud computing. The need for greener practices (like smart infrastructure) is urgent; this Superstream event will help you start implementing them. What you'll learn and how you can apply it Understand the environmental implications of software development and cloud operations and why it is so urgent to adopt more sustainable practices Learn how to reduce software emissions, optimize cloud resources, and measure your carbon impact using a variety of protocols, tools, and best practices Learn how to communicate with colleagues and leaders about green computing initiatives and become an advocate for sustainability in your organization This live event is for you because... You're a software developer or engineer working in the cloud and you want to build more responsible and efficient applications. You're a cloud architect, operations manager, or engineering leader responsible for helping your organization achieve its sustainability goals. You care about the planet and want to be a part of the solution in your organization. Recommended follow-up: Read Building Green Software (early release book) Watch Infrastructure & Ops Hour with Sam Newman: Cloud Providers and Sustainability with Anne Currie (video) Listen to Understanding Corporate Sustainability (audiobook).

Abstract: Join us for a special conversation with Sam Newman and software development pro Kevlin Henney, who'll discuss software design things that practitioners keep forgetting about and why good design matters so much. They'll also explore the idea of using the oft-cited "right tool for the job" and explain why that's so difficult to determine when the very process of development is what reveals "the job." This is a chance for you to hear from Sam and Kevlin about software development, how to use the right tools for your work, and their own career journeys. They'll spend a few minutes covering the trends that are influencing software, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Explore what really matters for software design See what's coming next for software development This recording of a live event is for you because... You want the chance to ask Sam Newman and Kevlin Henney your questions about software development. Recommended follow-up: Attend Software Development Superstream: Becoming a Senior Software Engineer (live event on February 22).

Abstract: Join us for a special conversation with Sam Newman and The Staff Engineer's Path author Tanya Reilly to learn why companies need engineers that contribute at a high level as role models—driving big projects, determining technical strategy, and raising everyone's skills. They’ll discuss the three key pillars of the staff engineer role: taking a broad, strategic view when thinking about your work; diving into practical tactics for making projects succeed; and determining what "good engineering" means in your organization. They’ll also explore what it means to be a leader without direct authority, how to plan ahead to make the right technical decisions, and how to make everyone around you better while still growing as an expert in your domain. Sam and Tanya will also talk about the staff engineer role, how to lead without taking the management track, or their own career journeys. They’ll spend a few minutes covering the trends that are influencing software, then tell you what you need to know to stay ahead of the curve.

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

Abstract: Sponsored by F5 and Orca Security Many organizations today find themselves in a hybrid or multicloud environment, whether they planned it or just stumbled into it. But juggling workloads across these complex architectures is an incredibly tricky business. From isolated silos to costly resource sprawl, the challenges are immense. The supercloud has arrived on the scene to help, providing a layer of abstraction on top and offering a consistent way to manage it all. However, there's a lot of mystery still swirling around about what the supercloud is exactly and how it works. Join our expert speakers as they shed light on the different approaches to managing combined or multiple private, public, and edge clouds. They'll demystify common terms and concepts, help you gain a better understanding of what these various cloud models look like in practice, and show you how to successfully plan for, deploy, monitor, and secure these complex cloud architectures of the future. What you'll learn and how you can apply itUnderstand the various cloud deployment models and the opportunities and challenges of combining different types of cloud services and infrastructure Learn how to prepare for the complexities of hybrid or multicloud systems and identify the best solutions for your business or professional needs This recording of a live event is for you because... You're a developer, architect, engineer, or decision maker working with complex cloud environments. You want to be able to manage or leverage multiple cloud services and stay up-to-date on the latest developments in cloud technologies. Recommended follow-up: Read Cloud Without Compromise (book) Read Hybrid and Multicloud Management (report) Watch Infrastructure & Ops Hour: Multicloud with Gregor Hohpe (video) Take Multicloud Strategy Choices and Trade-Offs (live online training with Rashmi Tambe and Sunit Parekh) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

Abstract: Look no further for the 2023 audio-only collection of O'Reilly Book Club interviews. Hear directly from our authors about their book writing processes and gain insight into how they've become the subject matter experts in their fields.

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: Join us for this edition of O'Reilly Book Club with Sam Newman, author of Building Microservices, to learn what microservices are and determine if they're the right choice for your system. You'll discuss the essence of microservice architecture with Sam and your peers while exploring the core concepts that make microservices work and the impact that microservices have on various aspects of software delivery. Plus you can hear from Sam about Building Microservices to better understand whether microservices are right for you. What you'll learn and how you can apply it Understand what microservices are and why they're so popular Determine whether they're right for you This recording of a live event is for you because... You want to go beyond the words on the page and hear from the expert author. You want to learn from others interested in microservices. Recommended follow-up: Read Building Microservices or listen to the audiobook Attend Microservices in 3 Weeks (live online training with Sam Newman).

Abstract: Join us for a special conversation with Sam Newman and tech leader Pat Kua, where they'll discuss why excellence in software engineering matters more today than ever--and why it's important to continually hone your craft. They'll also explore how engineering practices have evolved and what that implies for the future. This is a chance for you to hear from Sam and Pat about software development, how to use the right tools for your work, and their own career journeys. They'll spend a few minutes covering the trends that are influencing software, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Learn what really matters for software design Find out what's coming next for software development This recording of a live event is for you because... You want the chance to hear from Sam Newman and Pat Kua about software development. You want to keep up with the latest developments in engineering practice. Recommended follow-up: Read Building Evolutionary Architectures, second edition (book) Listen to The Manager's Path (audiobook) Read The Staff Engineer's Path (book).

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: 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: 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: 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: The best time to get started with cybersecurity is now. And the best way to get started is as a team. Join Sam Newman and SafeStack founder and CEO Laura Bell for a special conversation on cybersecurity. They'll discuss why, more than ever, it's crucial that organizations big and small take whatever steps they can to keep their data, people, and systems safe. They'll also explore how secure engineering practices have evolved and what that implies for the future. This is a chance for you to hear from Sam and Laura about software development, cybersecurity, and their own career journeys. They'll spend a few minutes covering the trends that are influencing software, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Learn what really matters for software design Find out what's coming next for software development This recording of a live event is for you because... You want the chance to hear from Sam Newman and Laura Bell your about software development. Recommended follow-up: Listen to The Manager's Path (audiobook) Read Building Microservices, second edition (book) Read Security as Code (book).

Abstract: Join us for a special conversation with Sam Newman and software architect Nathaniel Schutta of VMware, who'll discuss what it means to be a successful architect--and how you can start working toward that goal. Learn the skill sets you'll need to juggle multiple priorities, meetings, and time demands; get tips for making effective presentations and creating clear architecture documents; and discover reliable techniques for managing stakeholders and building relationships. This is a chance for you to hear from Sam and Nathaniel about software development, their own career journeys, and how to begin making your move from developer to architect. They'll spend a few minutes covering the trends that are influencing software, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Gain insight into a software architect's role and its rewards and challenges Chart your own path for professional advancement See what's coming next for software development This recording of a live event is for you because... You want to take the next step in your career. You want the chance to hear from Sam Newman and Nathaniel Schutta about software development. Recommended follow-up: Listen to The Software Architect Elevator (audiobook) Read Software Architecture Patterns, second edition (book) Listen to Fundamentals of Software Architecture (audiobook).

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: 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: Software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life. So software engineers don't just need top-notch programming skills--they also have to understand how to develop proper engineering practices to make their codebase sustainable and healthy. That's the difference between programming and software engineering. Whether you're a freshly minted software engineer or a seasoned pro, these expert-led sessions are sure to give you insight into the fundamental principles that should be top of mind when you're designing, architecting, writing, and maintaining code. What you'll learn and how you can apply it Learn how to optimize your VS Code development environment and to refactor an existing code base with Rust Understand how a shift-left testing approach can create quicker feedback loops and how you can improve your software performance and design starting with making small changes to code (tidyings) This live event is for you because... You're a software developer or engineer looking for ways to write and refactor code faster and with fewer errors. You want to learn how to use new tools and programming languages. Recommended follow-up: Read The Staff Engineer's Path (book) Read Software Engineering at Google (book) Listen to The Manager's Path (audiobook) Read Fundamentals of Software Engineering (early release book).

Abstract: Join us for a special conversation with Sam Newman and technical coach Emily Bache, who'll discuss why software teams that work well together produce truly great software. They'll also share expert insights on ways to improve cooperation among teams at your own organization. They'll explore why writing clean code matters and why high-quality automated tests, frequent integration, and small but continual design improvements can enable organizations to build new, higher-quality features more quickly. This is a chance for you to hear from Sam and Emily about software development, the challenges of meshing teams into a cohesive whole, or their own career journeys. They'll spend a few minutes covering the trends that are influencing software, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it What really matters for software design See what's coming next for software development This recording of a live event is for you because... You want the chance to hear from Sam Newman and Emily Bache about software development. Recommended follow-up: Read Clean Code Cookbook (book) Listen to Effective Software Testing (audiobook) Read Full Stack Testing (book).

Abstract: This is the one stop shop for all Software Development Hour interviews of 2023 in their audio format. Keep up-to-date with Sam Newman and his colleagues on their software development journeys.

Abstract: As software development grows more complicated and becomes increasingly central to a business's identity, the demand is high for developers who operate at a senior level. Join us to level up your skills and accelerate your journey to senior software engineer. These in-depth sessions cover some of the biggest challenges facing software developers today, teaching you practical methods and best practices to improve coding and software design, better manage data, mentor new engineers, and collaborate with your team. About the Software Development Superstream Series: This series will help you elevate your technical skills, become a better project manager, and build the other professional skills that will allow you to move into senior engineering roles. What you'll learn and how you can apply it Learn how to contribute at a high level, drive big projects, and determine tech strategy Understand what's really important for career development Determine what you should be working on, set your goals, and define your backlog of work This recording of a live event is for you because... You're a developer who wants to find your skills gaps and upskill accordingly to move to the senior or staff level. You want to better understand what work matters the most at every stage of your career and learn how to build the skills you need to support your journey. Recommended follow-up: Read The Staff Engineer's Path (book) Read Software Engineering at Google (book) Listen to The Manager's Path (audiobook) Read Mentoring (book) Take From Developer to Software Architect (live online training course with Nathaniel Schutta) Take Fundamentals of Software Engineering in 3 Weeks (live online training course with Nathaniel Schutta) Take Hands-On Software Design (live online training course with Venkat Subramaniam) Take Introduction to Critical Thinking (live online training course with Connie Missimer) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

Abstract: Join us for a special conversation with Sam Newman and Marianne Bellotti, best-selling author, builder of the data infrastructure for the United Nations, and fixer of some of the oldest and most complicated computer systems in the world as part of United States Digital Service. They'll discuss how to tame and modernize complex systems and explain why any kind of modernization or large-scale migration requires thinking about the people side of the problem in addition to the technical challenges to ensure success. This is a chance for you to from Sam and Marianne about software development, how to best manage migrations, and their own career journeys. They'll spend a few minutes covering the trends that are influencing software, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Learn what really matters for software design Discover best practices for modernizing complex systems Find out what's coming next for software development This recording of a live event is for you because... You want the chance to hear from Sam Newman and Marianne Bellotti about software development. You want to keep up with the latest developments in engineering practice. Recommended follow-up: Read Building Evolutionary Architectures, second edition (book) Listen to The Manager's Path (audiobook) or read the book Read The Staff Engineer's Path (book).

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: 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: 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: 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 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: 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: 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: Join us for a special conversation with Sam Newman and Gaurav Sen, founder and CEO of InterviewReady. They'll chat about system design and the system design interview, including how to prepare for the interview as a candidate and how to evaluate candidates correctly, as well as the competencies that are most important to test in an interview. You'll also hear what they think about the possibility of automated judges for system design interviews. This is a chance for you to hear from Sam and Gaurav about software development, how to begin making the move from developer to architect, and their own career journeys. They'll spend a few minutes covering the trends that are influencing software and then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it What really matters for system design See what's coming next for software development This recording of a live event is for you because... You're preparing for an interview and want advice from an expert. You want the chance to ask Sam Newman and Gaurav Sen your questions around software development and system design. Recommended follow-up: Watch System Design Fundamentals (on-demand course) Listen to Effective Software Testing (audiobook) Read Head First Software Architecture (book).

Abstract: You've got your Kubernetes cluster up and running. . .so what's next? You can do much more with Kubernetes than just manage containers. These expert-led sessions will show you how. Join us to keep up with Kubernetes. You'll learn practical strategies and techniques (like how to build K8s into your own developer platform and how to use it on a public cloud), get insight into doing serverless on Kubernetes, and get a glimpse of what the future holds for this widely popular tool. What you'll learn and how you can apply it Understand the benefits and pitfalls of working with Kubernetes Learn how tooling can help with multicluster management This live event is for you because... You're a developer who wants to learn more about developer platforms built on top of Kubernetes so that you can have the tools you need when you need them. You want to use Kubernetes to benefit or improve reliability, velocity, security, and more. You want to learn more about MLOps and the Kubernetes tools ecosystem. Recommended follow-up: Read Kubernetes Up and Running, third edition (book) Explore Certified Kubernetes Application Developer (CKAD), second edition (video course) Watch GitOps and Kubernetes (video edition) Read Introducing MLOps (book) Watch Infrastructure and Ops Hour: Platform Engineering with Camille Fournier (video) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

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 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: 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: 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: Microservice architectures are increasingly popular, but they bring with them increased complexity and new challenges. One of the more challenging areas with any microservice style architecture is security; application security is different than with a monolith, protecting data in transit and at rest, and protecting your microservices whilst still allowing a high degree of independence. With more moving parts, understanding what security posture is required for your microservices architecture can be hard to understand. Join expert Sam Newman where he will show you that while microservice architectures can present more challenges regarding the security of our applications they also give us more ways to build and operate secure systems. At the end of the class you'll have a better appreciation for security best practices for microservice style architectures and where to spend your time to deliver the right level of security for your microservice architecture. What you'll learn and how you can apply it: Understand the functions and principles of microservice security, and how microservice architectures change some of the common challenges of application security Understand how to use threat modeling, trust The challenges of patching microservices, and how to handle secrets What types of protection may be needed to protect data in transit and at rest How to identify where technologies like JWT or Open Policy Agent can be used in the context of authentication and authorization This course is for you because: You have a microservice architecture and are worried it isn't secure You're planning a microservice architecture and don't know where to start regarding security You're a developer or architecture trying to build more skills in the area of security, so you can build security thinking into how you build your system Prerequisites: Awareness of what microservices are.

Abstract: "Distributed systems have become more fine-grained in the past 10 years, shifting from code-heavy monolithic applications to smaller, self-contained microservices. But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures. Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You'll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain." --

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: 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: Observability-a measure of how well internal states of a system can be inferred from its outputs-is crucial for engineering, managing, and improving complex business-critical systems. Join us to learn how observability can help any software engineering team gain a deeper understanding of system performance, so you can perform ongoing maintenance and ship the features your customers need. About the Infrastructure & Ops Superstream Series: This four-part Superstream series guides you through what you need to know about modernizing your organization's infrastructure and operations, with each event day covering different topics and lasting no more than four hours. They're packed with the expert insights, skills, and tools that will help you effectively manage existing legacy systems while migrating to modern, scalable, cost-effective infrastructures-with no interruption to your business. What you'll learn and how you can apply it Gain a deeper understanding of system performance so you can perform ongoing maintenance and ship the features your customers need Understand how to build an observability-driven development practice Discover how your production services are really performing right now This recording of a live event is for you because... You're a developer who wants to learn the basics of observability and how to use it in your system. You want to better understand how observability can be used with data. You want to know what the future holds for observability and infrastructure and operations. Recommended follow-up: Read Observability Engineering (book) Read Kubernetes Security and Observability (book) Watch Observability at Google (video) Read Linux Observability with BPF (book) (Watch Case Study: How Lightstep Implemented Observability (recorded event)).

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: 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: Incidents are inevitable in complex systems, but learning from these events shouldn’t require assigning blame. Workers on the front lines have much to contribute to a company’s understanding of how failures happen—and to how to prevent them from happening in the future. Join us for a special conversation about resilience engineering with Sam Newman and incident analysis pro Jessica DeVita. They’ll discuss what resilience engineering is and why it matters for infrastructure and operations in particular, walk you through how to learn from incidents while maintaining your teams’ cohesion, and explain how to use that knowledge to drive design decisions with intentionality. They’ll spend a few minutes covering the trends that are influencing infrastructure, then tell you what you need to know to stay ahead of the curve. What you’ll learn and how you can apply it Explore the origins of, need for, and challenges around incident analysis See what’s coming next for infrastructure and ops This live event is for you because… You’re looking for ways to improve your incident response and engineering environment. You want to learn about the foundations of resilience engineering, a discipline that combines safety science with human factors, and understand why resilience depends more on people than on technology. Recommended follow-up: Read 97 Things Every SRE Should Know (book) Read Incident Metrics in SRE (report) Watch Infrastructure & Ops Superstream Series: SRE Edition (recorded Superstream event)

Abstract: A walkthrough of building a basic phrase repeater console application in VS Code 2022, .NET 6 and C# 10

Abstract: What are the three most important files in a Python project? * Makefile * Dockerfile * Requirements

Abstract: How to use ~/.bashrc to manage project secrets

Abstract: Find out what Github Codespaces is and how to use it to write Python in under 2 minutes

Abstract: Learn to perform Continuous Delivery of Container Based Projects using ECR, Cloud9 and App Runner. 00:00 Intro 00:27 Architectural Overview 01:30 FastAPI project overview 01:50 Setup AWS Cloud9 03:20 Setup ECR 05:00 Setup AWS App Runner

Abstract: Learn to use AWS Storage Solutions Correctly. Hi, my name is Noah gift, and today I'm going to talk about AWS storage systems. We're going to talk about the elastic box system where EBS, also S3, the object storage system, which has unlimited data storage, and also EFS, the elastic file system. And finally, offsite backup, and also archiving systems with glacier, we're also going to do some demos of those products. Let's go ahead and get started. This video shoes both theory and hands on demos. * EBS (Elastic Block Storage) * EFS (Elastic File System) * S3 (Object Storage) * Glacier (Archiving) 00:00 Intro 00:49 Storage Module Overview 03:00 What is EBS? 11:00 EBS Demos 30:00 What is S3? 38:00 S3 Demos 48:00 Boto3 S3 Demos 49:00 What is EFS? 51:47 What is AWS Glacier?.

Abstract: Learn to deploy containerized Microservices using Cloud9, ECR, App Runner and FastAPI automatically with AWS Code 00:00 0:37 Continuous Delivery Architecture 01:06 AWS App Runner 01:41 Building Containerized Microservices with FastAPI 03:22 Pinning requirements.txt to a specific version 06:10 Running FastAPI 10:40 Setup ECR 14:19 Setup ECR with AWS App Runner 16:10 Create containerized Flask API Microservice in Github Codespaces 18:54 Testing Swagger UI in Github Codespaces 20:11 Verify FastAPI Microservice in AWS App Runner 22:20 Setup AWS Code Build for Continuous Deployment with App Runner 30:12 Architectural Overview of Continuous Deployment 32:35 Verify Continuous Deployment with AWS Code Build and App Runner.

Abstract: Learn to refactor a Python script into a library called by Python Click CLI. 00:00 Intro 00:19 Refactoring to a library 01:44 Installing click 02:23 Importing refactored library 02:36 Building click options 05:04 Formatting code with Python Black and Running Click 06:14 Building conditional logic to print colored output.

Abstract: Learn to build AWS Step Functions with Python and AWS Lambda. Use AWS Cloud9 to test your code locally and the Step Functions console to deploy your code to AWS. 00:00 Intro 00:22 Create AWS Lambda 02:49 Build Fruit Generator 05:01 Create New Test Event 07:18 Invoke AWS Lambda in Cloud9 09:32 Create AWS Step Functions 10:51 Create Second AWS Lambda 11:57 Create test payloads for second AWS Lambda 13:00 Build out the second AWS Lambda logic 15:11 Test bad logic condition 15:30 Build out chain reaction of AWS Step Functions.

Abstract: Learn to build cloud pipelines with AWS Step Functions 00:00 Intro 01:00 Create AWS Lambda function in Python 04:00 Create return statement that returns JSON depending on type of event 05:49 Test the AWS Lambda function 08:00 Build a second AWS Lambda function that can parse first function 13:00 Create AWS Step Function that consumes both AWS Lambda functions for Pipeline.

Abstract: GitHub Codespaces and custom dotfiles Add your dotfiles to any Codespace automatically Customize any GitHub Codespace you create or use by automatically getting your dotfiles in there with no effort! You only need a GitHub repository that contains your dotfiles to get this feature enabled in any Codespace you work on You also have the ability to have a setup.sh script that you can use to further customize how GitHub will add your dotfiles to your Codespace at creation time. Learning Objectives In this lesson you will learn: Configure a GitHub Codespace with dotfiles Create a repository with your own dotfiles Additional features you can try with dotfiles in Codespaces Useful Resources Dotfiles and Codespaces documentation Free Azure Certification for Students Introduction to GitHub Actions Run Python In GitHub Actions.

Abstract: Learn to use AWS to continuously deploy a Hugo site that has global scale. 00:00 Intro 02:00 Create Github Repo 05:52 Launch AWS Cloud9 05:58 Download Hugo binary 11:00 Create Hugo Quickstart 17:00 Adding submodules for theme 23:00 Building Hugo locally and running it in Cloud9 26:00 Setup AWS S3 Static Hosting 30:30 Setup AWS CloudBuild for Continuous Delivery of Hugo 40:00 Verify Hugo deploy works.

Abstract: Learn to pass the AWS ML Certification 00:00 Intro 03:00 AWS ML Certification Course Outline 05:21 What is the Data Scientist role? 05:58 Machine Learning engineer 06:33 Applied science researcher 07:08 Machine learning developer role 08:05 Resources and documentation 10:48 AWS SageMaker Studio Lab 13:18 AWS Machine Learning Lens.

Abstract: Learn to use a CUDA GPU to speed up code in Python dramatically. CUDA POWERED! This video will show you how to use CUDA GPUs with Python. Topics Covered Include: 00:00 Introduction 00:16 End of Moore's Law 01:15 What is a TPU and ASIC 02:25 How a GPU works 03:05 Enabling GPU in Colab Notebook 04:16 Using Python Numba 05:40 Building Mandlebrots with and without GPU and Numba 07:49 CUDA Vectorize Functions 08:27 Copy Data to GPU Memory Learning Objectives Learn about the End of Moore's Law and ASICs Learn to compare the performance of GPUs and TPUs, and JIT compilers Build your own vectorized functions with Numba and CUDA to speed up your code with GPUs 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: Assimilate Python From Zero Learn Python From the Absolute Beginning This video series covers Python from the absolute beginning with incremental weekly lessons. Introduction Python Basics and How To Run Python Topics Covered Include: Python Basics Python Syntax Mastering Python Learn Python week-by-week Python Strings 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: Build Real-World AWS Microservices with Python and FastAPI From Zero. Practice end-to-end DevOps from scratch! This video will show you how to start from the absolute beginning of DevOps and build a real-world AWS microservice with Python and FastAPI. Topics Covered Include: 00:00 Introduction 01:00 Learning to use Github CodeSpaces 03:00 Building Python Project Scaffolding 06:50 Building Python virtualenv 09:00 Adding a Python Dependency 22:58 Setup GitHub Actions 34:00 Running Pylint on your project 42:00 Using a library you created 46:00 Building library tests with Pytest 51:00 Building CLI tools with Python Fire 59:00 Using IPython with libraries 01:02:09 Exploring Python wikipedia library 01:08:00 Using FastAPI and uvicorn 01:15:00 Exploring FastAPI Swagger API docs for microservice with wikipedia library 01:18:00 Adding NLP with textblob library in Python 01:29:00 Running tests with Pytest 01:34:00 Integrating Docker with FastAPI 01:50:00 Using AWS ECR (Elastic Container Registry) with FastAPI 01:52:00 Integrating AWS CodeBuild for Continuous Delivery to ECR Learning Objectives Using AWS to build real-world microservices Deploying AWS microservices with AWS CloudBuild and AWS App Runner for FastAPI Practice end-to-end DevOps from scratch with Python and FastAPI 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: Join us for a special conversation on the extended Berkeley Packet Filter (eBPF) with Sam Newman and Isovalent chief open source officer Liz Rice. You'll learn how eBPF has gone from relative obscurity to one of the hottest technology areas in modern infrastructure computing, why the ability to dynamically change the kernel behavior is so useful (and why eBPF is such a game changer), and much more. Sam and Liz talk about eBPF, container security, infrastructure and ops, and their own career journeys. They'll also spend a few minutes covering the trends that are influencing infrastructure, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Explore the origins of and need for eBPF See what's coming next for infrastructure and ops This recording of a live event is for you because... You want to better understand how to implement eBPF at your organization. You're looking for ways to improve your software delivery time and team structure. Recommended follow-up: Read What Is eBPF? (report) Read Container Security (book) Read Security Observability with eBPF (report) Attend Infrastructure & Ops Superstream: Linux Fundamentals (live event on September 14).

Abstract: 52 Weeks .NET - The Series Iterative .NET Live Coding 1.0 52 Weeks Live coding NET ep1- Setup Github CodeSpaces for .NET 2.0 52 Weeks Live coding NET Episode2 - Going through Microsoft tutorial on CSharp 3.0 52 Weeks Live coding NET Episode3 - Running Blazor on .NET Core 4.0 52 Weeks of Live Coding NET Episode 4 - Starting with CDK and Failing 5.0 52 Weeks of Live Coding NET Episode 5 - Building a CDK App and Succeeding 6.0 52 Weeks net EP6 more cdk2.0 - Trying a more complicated CDK app and Failing Topics include CSharp Blazor .NET Core CDK 2.0 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: Iteratively Build NLP Tools and FastAPI Microservice on AWS From Zero From Zero to NLP Hero This video will show you how to use CUDA GPUs with Python. Lessons Covered Include: 1.0 Introduction to Course 1.1 Introduction to Python Statements with Colab, IPython and GitHub CodeSpaces 2.0 Introduction to Python functions from simple to complex with Closure, and Decorators 3.0 Build a simple NLP Tool with TextBlob, Wikipedia and Python Fire command-line tool 4.0 Build an end-to-end NLP Microservice with FastAPI, ECR and AWS App Runner. Learning Objectives Learn key software engineering principles and best practices for building software. Learn to build NLP tools using TextBlob and Wikipedia. Learn to build a FastAPI containerized Microservice deployed via Amazon ECR and AWS App Runner. 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: 52 Weeks of Swift Learning Swift by Live Coding This video series live coding Apple's Swift language and iteratively learning the language. Lessons Covered Include: 1.0 52 Weeks of Swift Episode 1 getting setup 2.0 52 Weeks of Swift Episode 2 the basics 3.0 52 Weeks of Swift Episode 3 basic operators 4.0 52 Weeks of Swift Episode 4 strings characters 5.0 52 Weeks of Swift Episode 5 collection types 6.0 52 Weeks of Swift Episode 6 Functions 7.0 52 Weeks of Swift Episode 7 Closures 8.0 52 Weeks of Swift Episode 8 Enumerations 9.0 52 Weeks of Swift Structures and Classes 10.0 52 Weeks of Swift Episode 10 Properties 11.0 52 Weeks of Swift Episode 11 Methods 12.0 52 Weeks of Swift Episode 12 Subscripts 13.0 52 Weeks of Swift Episode 13 Inheritance 14.0 52 Weeks of Swift Episode 14 Deinitialization 15.0 52 Weeks of Swift Episode 14 Initialization 16.0 52 Weeks of Swift_ Episode 16 Error Handling 17.0 52 Weeks of Swift_ Episode 17 Concurrency 18.0 52 Weeks of Swift_ Episode 18 Type Casting 19.0 52 Weeks of Swift_ Episode 19 Nested Types 20.0 52 Weeks of Swift Generics 21.0 52 weeks of Swift EP21 Protocols 22.0 52 weeks of Swift OpaqueTypes Learning Objectives Learn Apple's Swift language by Live Coding 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: 52 Weeks of EIL (Exploring Interesting Languages) Learning Interesting Languages Live Coding This video series live coding languages iteratively thus learning the language. Lessons Covered Include: 1.0 52 weeks of exploring interesting languages Episode 1 Julia installing getting started 2.0 52 weeks of exploring interesting languages Episode 2 Julia strings 3.0 52 weeks of exploring interesting languages Episode 3 Julia functions 4.0 52 weeks of exploring interesting languages Julia Episode 4 Julia piping vectorizing functions 5.0 52weeks EIL Julia EP5 Control Flow Learning Objectives Exploring interesting languages and frameworks Learning to code in Julia 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: The cloud is likely a major part of your IT infrastructure (or will be soon). And there's a good chance that Amazon Web Services--the current leader in the space--plays a role. Keeping up with best practices, new tools, and updates to existing tools is critical to getting the most from your cloud deployments, but it's quite a task. We'll help make it easier, with AWS-focused sessions on migrating workloads, operating AWS with a hybrid cloud or multicloud, and harnessing serverless for better performance. What you'll learn and how you can apply it Learn how to optimize cost and performance with the Graviton processor architecture. Use the three tenets of multicloud frameworks to build your cloud strategy. Understand how the Lambda platform integrates with other AWS services. This recording of a live event is for you because... You're a developer or engineer who wants to understand the challenges of working within the AWS platform. You want to become more proficient in identifying AWS services to help you make informed decisions about IT solutions based on your business requirements. You want to get started with AWS. Recommended follow-up: Read AWS Cookbook (book) Read Programming AWS Lambda (book) Watch "23.4 Demo: Systems Manager Run Command (CLI)" (video chapter from Amazon Web Services (AWS), third edition).

Abstract: Kubernetes for Data Learning Kubernetes For Data This video series covers the Kubernetes ecosystem for data. Lessons Covered Include Six Key Lessons: 1.0 What is Kubernetes? 1.1 Cluster Architecture 1.2 Pods and Nodes 1.3 Services and Deployments 2.0 Running Kubernetes with Minikube 3.0 3.0 4.0 5.0 1.1 Docker Container Demo 1.2 Minikube Demo 1.3 Minikube Dashboard 1.4 Deploying a containerized FastAPI App with Kubernetes Learning Objectives Learn Kubernetes for Data Learning to build solutions with Kubernetes for Data Learning the key syntax and features of Kubernetes for Data 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: GitHub Copilot Driven: Python DevOps from Functions to Continuous Delivery of Microservices on AWS Learn to use Python for DevOps and build a GitHub copilot driven microservice on AWS Noah Gift is the author of a course on Python for DevOps using GitHub Copilot. He explains how to deal with the file system, how to set up continuous integration, and how to build command line tools that help you automate your workflow. Noah explains some of the tools for building DevOps workflows on GitHub and wraps the course up with a FastAPI Microservice deployed on AWS using AWS App Runner. Topics Covered Include: Containers GitHub Actions GitHub Copilot GitHub Codespaces AWS App Runner Containers FastAPI Continous Integration and Continous Delivery Python DevOps DevOps Skills with the Python Ecosystem 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: Assimilate F Learning Fsharp During Live Coding This video series covers live coding the Fsharp Language iteratively thus learning the language. Lessons Covered Include: 1.0 Setup Fsharp in Visual Studio Code and GitHub Codespaces and build interactive Fsharp scripts and projects Learning Objectives Learn Fsharp Learning to build solutions with Fsharp Learning the key syntax and features of the FsharpLanguage 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: Assimilate Bash Learning Bash During Live Coding This video series covers live coding the Bash Language iteratively thus learning the language. Lessons Covered Include: 1.0 Setup Bash GitHub Codespace for Bash and then build a phrase repeator cli with help menu and error handling Learning Objectives Learn Bash Learning to build solutions with Bash the shell Learning the key syntax and features of the Bash 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: MLOps is consistently one of the greatest challenges engineers face when creating and maintaining machine learning systems. Join expert practitioners to learn techniques and best practices for operationalizing machine learning models and explore case studies of them in action, showing you what works--and what doesn't. What you'll learn and how you can apply it Understand MLOps processes for model deployment, containerization, and automation as well as monitoring, continuous experimentation, and improvement Learn how an understanding of SRE and DevOps principles can enhance the practice of MLOps Avoid common pitfalls in the process of building end-to-end machine learning pipelines This recording of a live event is for you because... You're a data or machine learning practitioner who puts machine learning models into production, or you're embarking on an MLOps career path. You want to improve your process of productionizing machine learning models by applying new techniques and best practices. Recommended follow-up: Read Practical MLOps (book) Read Reliable Machine Learning (book) Watch Radar Talks: Hugo Bowne-Anderson on MLOps Versus DevOps (video) Take Practical MLOps (live online course with Noah Gift) Take Open Source MLOps in 4 Weeks (live online course with Alex Kim) Read Site Reliability Engineering (book).

Abstract: Azure PostgreSQL Setup and deploy an Azure PostgreSQL database Learn how to setup a PostgreSQL database using the Azure cloud. From the different options you have to create a PostgreSQL database (flexible or single server) to connection strings and firewall settings. This video will walk you through all you need to know to setup the resources, understand the constraints, and then correctly connect from a remote workstation using psql . Learning Objectives In this video you will learn to: Use the Azure Portal to create a PostgreSQL database Select between single and flexible server options Understand the constraints to create a database Setup firewall settings for external access Use psql to connect from a remote workstation to PostgreSQL Use the default database to connect Resources Azure Fundamentals Certification Azure Fundamentals quick reference guide Azure remote compute for VSCode Automated Azure resource cleanup Learn Azure ML (AutoML) in One hour.

Abstract: Assimilate Data Science Projects Assimilate Data Science Projects During Live Coding This video series covers live coding data science projects iteratively and learning the language. Lessons Covered Include: 1.0 Exploring life expectancy data globally using Jupyter and Pandas Learning Objectives Learn how to use Jupyter and Pandas to explore data and explore data science projects Learning to build solutions for data science projects Learning the key syntax and features of the Python 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: Assimilate Google Cloud Learning During Live Coding This video series covers live coding the Language iteratively thus learning the language. Lessons Covered Include: 1.0 getting started Google Cloud shell apis cloudrun Learning Objectives Learn Google Cloud Learning to build solutions with Google Cloud Learning the key syntax and features of the Python Language on 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: AWS Certified Advanced Networking - Specialty (ANS-C01)-2023 Learning AWS Certified Advanced Networking This video series the AWS Certified Advanced Networking Certification 2023 Lessons Covered Include: 1.0 course intro 1.1 sap prerequisite 1.2 Domain intro 1.3 CDN Pattern 1.4 ELB Design 1.5 Amazon API Gateway 1.6 Route 53 Demo 1.7 Public vs Private Hosted Zones DNS-DEMO 1.8 Load Balancing Layer 3, 4, 7 of OSI Model 1.9 Cloudwatch Metrics Demo 1.1 Layer 1/2 concepts: VLAN, Jumbo Frames 1.11 Multiple AWS Accounts 1.12 VPC Peering 2.0 domain intro 2.1 Infrastructure Automation (IAC) with CDK Demo 2.2 Hybrid Networks 2.3 Authentication and Authorization 2.4 Network Monitoring 2.5 Traffic Management DNS 2.6 AWS Boto3 Cloud9 CodeWhisper Demo 2.7 AWS CLI Demo 3.0 domain intro 3.1 Quotas and Limits in AWS Networking 3.2 Inter-Regional communication patterns 3.3 Network performance testing tools- demo 3.4 VPC Flow logs - Demo 3.5 Different types of Network interfaces AWS 3.6 High-Availability via Route 53 4.0 domain intro 4.1 common security threats 4.2 network acls 4.3 AWS Cloud Trail - Demo 4.4 AWS Trusted Advisor Demo 4.5 Network encryption options AWS 4.6 AWS Shared Security Model 5.0 conclusion Learning Objectives Network Design (25%) Network Implementation (25%) Network Management and Operations (25%) Network Security, Compliance, and Governance 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: Assimilate GitHub Learning GitHub During Live Coding This video series covers live coding GitHub iteratively thus learning the platform. Lessons Covered Include: 1.0 ep1 getting started with GitHub Codespaces Actions Learning Objectives Learn GitHub Learning to build solutions with GitHub Learning the key technologies of GitHub like Actions, Codespaces, and more 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: Assimilate Typescript Learning Typescript During Live Coding This video series covers live coding the Typescript Language iteratively thus learning the language. Lessons Covered Include: 1.0 Setup Typescript in GitHub Codespaces compile and run hello world examples in the browser and with Node.js Learning Objectives Learn Typescript Learning to build solutions with Typescript Learning the key syntax and features of the Typescript 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: Assimilate Haskell Learning Haskell During Live Coding This video series covers live coding the Haskell Functional Programming Language iteratively thus learning the language. Lessons Covered Include: 1.0 Getting started with Haskell in GitHub Codespaces Learning Objectives Learn Haskell Learning to build solutions with Haskell Learning the key syntax and features of the Haskell 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: Join us for a special conversation on the extended Berkeley Packet Filter (eBPF) with Sam Newman and Isovalent chief open source officer Liz Rice. You'll learn how eBPF has gone from relative obscurity to one of the hottest technology areas in modern infrastructure computing, why the ability to dynamically change the kernel behavior is so useful (and why eBPF is such a game changer), and much more.

Abstract: Transformation is no longer a short-lived initiative. It is not a program.It is not linear.Instead, the world’s leading organizations now embrace transformationas a a challenging, stretching, exciting and essential constant in theirlives. Welcome to the age of perpetual transformation.Now, the Brightline Initiative and Thinkers50 have collaborated to bringtogether some of the world’s leading minds on the theme of perpetualtransformation. Curated by Thinkers50 cofounder Stuart Crainer andintroduced by PMI COO Michael DePrisco, Perpetual Transformationfeatures ideas and insights from Didier Bonnet, Susie Kennedy, KaihanKrippendorff, Jeffrey Kuhn, Habeeb Mahaboob, Tony O’Driscoll,Martin Reeves, Lars Fæste, Tom Deegan, April Rinne, Antonio Nieto-Rodriguez, Gabriele Rosani, Paolo Cervini, Robin Speculand, BehnamTabrizi and a host of others.

Abstract: Learn to prototype Amazon Web Services (AWS) ai and ml apis using awscloudshell and bash.

Abstract: Building AI APIs with .NET 6 and AWS Comprehend

Abstract: Learn to build an S3 Bucket Lister Console app using VS 2022 and AWS targeting .NET 6.

Abstract: Build a robust Python CLI tool with argparse The argparse module is part of the Python standard library and meant to help you build robust command line tools. Once you need flags, switches, values, or positional arguments, it is very difficult to achieve that without using a framework. In this case, argparse can help build all you need to handle inputs in the terminal. We'll see how a single file named size.py that calculates file sizes can make use of argparse to handle the input in the terminal. Then, we will cover how error handling is done automatically when the expectations from argparse aren't met. And finally, we'll go through some of the help menu options that construct the body of the help output. Check the resources section for the GitHub repo with sample code Why would you want to use argparse Since argparse is part of the Python standard library, there is no need for you to define or install any external dependencies. You are ensuring that any Python installation in any system will work correctly out of the gate. A very basic Python CLI tool without dependencies using the argparse module Next steps Now that you know how to enhance a Python script into a more powerful one with argparse , you can try out other frameworks like the Click framework or something much simpler by using the sys module. I have examples and guides for the sys.argv module and for using the Click framework . Useful links and resources GitHub repo with sample code Build Python applications from scratch Setup your Data Science environment with VSCode