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

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

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

Abstract: 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: This comprehensive course teaches you to leverage the power of cloud computing to develop production-ready machine learning solutions. Starting with the fundamentals of cloud storage, security, and infrastructure as code, you will gain a solid foundation in cloud computing concepts. The course then dives into serverless machine learning, teaching you to build and deploy ML models using popular cloud AutoML platforms like Google AutoML, Amazon SageMaker, Microsoft Azure ML, and CreateML. Through hands-on labs, you'll learn to train custom models with just a few lines of configuration, without needing deep ML expertise. Next, the course explores serverless technologies like AWS Lambda, Google Cloud Functions, and Azure Functions to cost-effectively operationalize your ML models at scale. You'll learn to expose your AutoML models as serverless microservices, automatically scaling to handle any load. The course also covers serverless data processing and ETL to build complete ML pipelines. Finally, you'll learn to apply DevOps best practices to your serverless ML applications using continuous integration and delivery (CI/CD), infrastructure as code, monitoring, and containerization technologies like Docker and Kubernetes. By the end, you'll have the skills to build highly scalable end-to-end machine learning solutions leveraging the latest cloud AutoML and serverless technologies.

Abstract: Providing a much-needed study on cybersecurity regime building, this comprehensive book is a detailed analysis of cybersecurity norm-making processes and country positions, through the lens of multi-stakeholder diplomacy. Multi-disciplinary and multi-national scholars and practitioners use insights drawn from high-level discussion groups to provide a rigorous analysis of how major cyber powers view multi-stakeholder diplomacy. Looking at how past cybersecurity initiatives and multi-stakeholder negotiations in other fields illuminate its dynamics, this book will help put states' approaches towards multi-stakeholder cyber diplomacy into perspective, and frame the role of private actors in cybersecurity regime building. Evaluating the most promising institutional arrangements and mechanisms for implementing cybersecurity, this book combines top-down analyses relevant to the design of international cybersecurity regimes with bottom-up case studies, tracing the approaches of important states towards multi-stakeholder participation in cyber diplomacy. With a wealth of policy-relevant findings, this book will be welcomed by practitioners and scholars of international law, international organisation and international cybersecurity as well as multi-stakeholder governance and multilateral regimes. Policymakers and diplomats involved in international cybersecurity processes will also benefit from its cutting-edge comparative analysis of the approaches of key cyber powers.

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

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

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

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

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

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: 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: "The Handbook on European Union Climate Change Policy and Politics provides a wide-ranging and in-depth assessment of current and emerging challenges facing the EU in committing to and delivering increasingly ambitious climate policy objectives. It traces the development of climate and energy policies since the early 1990s and examines their continued evolution in the context of the 2019 European Green Deal. With contributions from leading international scholars, it describes the key dynamics driving policy developments and the role of key actors in climate and energy-related policy processes. Covering topics that have previously been relatively neglected, or have recently gained greater significance, such as finance and investment, 'hard to abate' sectors and negative emissions, this timely Handbook offers an up-to-date and unrivalled exploration of the complexities of climate policymaking. It will be of primary interest to academics researching EU politics, and environmental politics, policy, regulation and governance more widely. It will be especially pertinent to students and researchers who require more specialized knowledge of EU climate policy and politics"--

Abstract: "In the face of major global demographic change, social care policy and practice are in urgent need of radical reform and reassessment. Rising poverty, inequality and pressure on local communities internationally, are also increasing the urgent need for reform. Drawing on the crisis-ridden UK experience as a case-study, this highly original book identifies the limits of the traditional welfare state in taking forward policy for the twenty-first century. The proposals amount to a renewed approach to social care, based on the philosophy of independent living as originally developed by the international disabled people's movement and subsequently embodied in a United Nations treaty applicable to all in need of care and support. Despite wide international sign up since adoption in 2008 there is little evidence of any nation successfully delivering. For the first time, this book offers both a blueprint for an environmentally sustainable, rights-based approach to social care and a practical route to achieving it"--

Abstract: "This forward-thinking book illustrates the complexities of the morality of human rights. Emphasising the role of human rights as the only true global political morality to arise since the Second World War, chapters explore its role as applied to often controversial issues, such as capital punishment, the exclusion of same-sex couples from civil marriage and criminal abortion bans. Clarifying and cross-examining the morality of human rights, Michael J. Perry discusses their connection to moral equality and moral freedom, as well as exploring the significance of anti-poverty human rights. This illuminating book concludes with an explanation as to why the morality of human rights is acutely relevant to challenges faced by humanity in the modern era. In particular, the challenges of growing economic inequality and climate change are emphasised as having profound relevance to the morality of human rights. Interrogating the Morality of Human Rights will be of great benefit to both undergraduate and graduate students who are contemplating the idea of human rights and their morality within their studies. Professors and academics with cause to study and research human rights would also find it to be of interest, particularly those in the field of legal scholarship"--

Abstract: "Nature-based solutions (NBS) are increasingly being adopted to address climate change, health, and urban sustainability, yet ensuring they are effective and inclusive remains a challenge. Addressing these challenges through chapters by leading experts in both global south and north contexts, this forward-looking book advances the science of NBS in cities and discusses the frontiers for next-generation urban NBS. NBS are fundamentally inter- and transdisciplinary approaches that require systems thinking and multi-level governance. With a focus on the multiple challenges that cities face, from heat and air pollution to storm water and threats to human health, this book puts forward a diversity of ideas for embracing complexity in mainstreaming NBS and inspiring new approaches to create the ecological urban futures we need. Speaking to the need for cities around the world to employ ecological, nature-based design, this book will be essential reading for early career professionals, practitioners, scholars, and students across multiple disciplines engaging with nature-based solutions including urban ecology, design, architecture, landscape architecture, geography, urban planning, policy, and management"--

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: 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: "Edward Elgar Publishing Ltd in partnership with United Nations Inter-Agency Task Force on SSE (UNTFSSE) The Encyclopedia of the Social and Solidarity Economy is a comprehensive reference text that explores how the social and solidarity economy (SSE) plays a significant role in creating and developing economic activities in alternative ways. In contrast to processes involving commodification, commercialisation, bureaucratisation and corporatisation, the SSE reasserts the place of ethics, social well-being and democratic decision-making in economic activities and governance. Identifying and analysing a myriad of issues and topics associated with the SSE, the Encyclopedia broadens the knowledge base of diverse actors of the SSE, including practitioners, activists and policymakers. Analysing the role of SSE organisations and enterprises in enhancing wellbeing, planetary health and democracy at various levels and their contribution to achieving the Sustainable Development Goals, the Encyclopedia invaluably summarises knowledge about the key aspects of the SSE. Accomplished researchers depart from traditional nationalistic, Eurocentric and trans-Atlantic perspectives to explain the SSE from a global perspective with a focus on untold stories of its development in both developing and developed countries. A collective work of the UN Inter-Agency Task Force on SSE (UNTFSSE), this Encyclopedia will serve as an essential tool for scholars and students of comparative social policy, international economics, management studies and economic sociology. Key Features: - 57 entries - Clearly organised into thematic sections addressing histories, concepts and theories, actors and organisations, development, and environment and governance - Breaks down the complex relationship between economic, social and political dimensions in an accessible way"--

Abstract: Skills and inequality have long been a central theme in analyses of social structure and economic development. A Research Agenda for Skills and Inequality offers an insightful cross-disciplinary framework for research on how unequal living conditions form, persist and change in interplay with human skill formation and development. Drawing on prominent new advances in the field, this incisive Research Agenda builds a forward-thinking framework for research. Spanning an extensive eighteen chapters, each examining a specific but major aspect of the general theme of skills and inequality, the book provides a comprehensive overview of links between the two. Against the backdrop of established insights from related but separate fields of inquiry, including economics, sociology, demography, human resource management, political science, philosophy and psychology, the Research Agenda presents an exciting overview of recent advances in analyses of skills and inequality. Opening vistas for future research based on extensive literature reviews and new findings, this Research Agenda offers compact, ground-breaking essays for students, policy makers, and advanced researchers in many disciplines including social policy, business management, and employment relations

Abstract: "Despite the broad engagement of higher education institutions in most social sectors, limited thinking and hyper-individualistic approaches have dominated discussions of their value to society. Advocating a more rigorous and comprehensive approach, this insightful book discusses the broad range of contributions made by higher education and the many issues entailed in theorising, observing, measuring and evaluating those contributions. Prepared by a group of leading international scholars, the chapters investigate the multiple interconnections between higher education and society and the vast range of social, economic, political and cultural functions carried out by universities, colleges and institutes and their personnel. The benefits of higher education include employable graduates, new knowledge via research and scholarship, climate science and global connections, and the structuring of economic and social opportunities for whole populations, as well as work and advice for government at all levels. Higher education not only lifts earnings and augments careers, it also immerses students in knowledge, helps to shape them as people, and fosters productivity, democracy, tolerance and international understanding. The book highlights the value added by higher education for persons, organisations, communities, cities, nations, and the world. It also focuses on inequalities in the distribution of that value, and finds that the tools for assessing higher education are neither adequate nor complete as yet. International and interdisciplinary in scope, this book will prove an invaluable resource to students and scholars of higher education, educational policy and social policy. It will also prove a useful resource to both university executives and tertiary education policymakers who want to make higher education more effectively accountable to the public"--

Abstract: "The global education crisis is a complex problem that requires change from teachers, school managers, civil society, implementers, planners, governments and donors. Addressing the issues that lie beneath this crisis requires new ways of working. Systems thinking is a suite of approaches to grappling with complex problems that is beginning to gain traction in international education. This book brings together new research in the nascent field of systems thinking in international education. Outlining the implications that systems thinking can hold for future research, practice and progress towards Sustainable Development Goal 4, a diverse range of leading scholars, policymakers and practitioners present novel research to encourage the shift from a linear view of change to a systems view. Chapters present diverse approaches to applying systems thinking in education across middle- and low-income countries, alongside research on how this has changed mindsets more widely. Questioning notions such as scaling and the universal applicability of 'what works', authors here suggest that locally relevant evidence and systemic rewards for using it are necessary to achieve SDG 4. This innovative book exemplifies how systems thinking offers the tools, frameworks and concepts to improve outcomes in education systems. With the education crisis further exacerbated by the COVID-19 pandemic, this timely book is essential reading for all those concerned with education and sustainable development goals. This thought-provoking book should be read by all those working to achieve SDG4; those whose day jobs inspire them and who look to their bookshelves for new ideas"--

Abstract: Feminist Frontiers in Climate Justice provides a compelling demonstration of the deeply gendered and unequal effects of the climate emergency, alongside the urgent need for a feminist perspective to expose and address these structural political, social and economic inequalities. Taking a nuanced, multidisciplinary approach, this book explores new ways of thinking about how climate change interacts with gender inequalities and feminist concerns with rights and law, and how the human world is bound up with the non-human, natural world. With contributions from leading scholars in law, feminism, human rights and politics, this book considers how equality is conceptualised experienced and used in policies, law and practice that are integral to climate justice. Chapters reveal how international and national policy and legal frameworks fall short on gender equality and climate justice. Overall, the book demonstrates that the climate crisis demands an ambitious and transformative approach to equality, including developing feminist ideas of care and social reproduction, to reconstruct law and policy towards a more just world for all. This ground-breaking book will be essential reading for scholars across many areas of law including environmental law, human rights, public international law, law and gender, and law and development. Its discussion of the international framework alongside in-depth case studies and assessments of women's mobilization strategies will also be highly relevant to social scientists, officials in international organizations, policymakers, lawyers and activists.

Abstract: "Reflecting on the depth of the experience with crises, this innovative book demonstrates what the world can learn from insights into crises from the Japanese perspective. Taking an institutionalist approach with a strong historical precedent, leading scholars in the social sciences and law explore how better to deal with both foreseeable and unforeseen crises. Illustrating their multifaceted and complex nature, the book examines a broad range of crises throughout history, including economic, fiscal and political crises; force majeure events such as pandemics and natural disasters; and military conflicts and acts of war. Chapters consider how various actors anticipate and deal with these crises, looking closely at their different perceptions of crisis and varying degrees of urgency. Analyzing institutional design and response, and the impact of psychological factors on disaster preparedness, the book considers how the decision-making capabilities of individuals can be enhanced to improve institutional capacity. Transdisciplinary, with an international reach, this topical book will prove invaluable to students and scholars across the social sciences, particularly those interested in Asian politics and environmental policy, disaster preparedness and institutional design. It also provides guidance for policymakers working in civil code reform"--

Abstract: "Shedding light on the future of urban spaces, this path-breaking book is a significant contribution to contemporary climate change scholarship. It synthesizes interdisciplinary research with practical policy, putting an emphasis on positive environmental and socially just outcomes and urban regeneration. Hot Cities offers insights from eminent academics and practitioners, providing both a practical and theoretical outlook on strategy development in a climate crisis. Chapters call for urgent responses to the urban heat problem, providing future projections to illustrate why this is important. They highlight that despite prominent issues within cities, such as maladaptive practices or unsustainable path dependency in city policy and planning, urban spaces are likely to be the safest and most protected locations from the uncompromising outcomes of global warming. This enlightening book will be incredibly useful for scholars of human geography, urban planning, climate adaptation and disaster risk reduction, environmental humanities, urban design and urban and regional studies. Due to its broad applicability, it will also benefit design practitioners and community developers"--

Abstract: "Teaching Federalism presents innovative ideas for teaching a wide variety of key concepts of federalism and federal-country cases. Each chapter introduces a topic, explains its place in federalism research, and provides learning objectives, pedagogical tools, and questions for class discussions, student essays, and examinations. Evaluation and reading suggestions are included as well. The book covers twenty substantive facets of federalism important for understanding contemporary issues of federalism and federation, such as power distribution, second chambers, high courts, intergovernmental relations, fiscal federalism, multinational federalism, conflict resolution, indigenous peoples, gendered federalism, and secession. Also included are case-study examples for teaching about federalism in Germany, India, Nigeria, Switzerland, and the United States. Educators around the world who teach federalism or wish to do so will find this a wonderful resource for lesson plans on a wide variety of issues related to federalism. Students studying federalism will also find it invaluable as an introductory resource for important topics and readings on the subject"--

Abstract: "This thoughtful book provides a refreshing, comparative perspective on the future of care homes in our post-pandemic world. Building on more than a decade of collaborative international and interdisciplinary research in Canada, Germany, Norway, Sweden, the UK and the US, it employs a feminist political economy framework to address the key challenges facing care homes in this turbulent era. With particular attention to lessons learned in Canada, Sweden, and Norway, the contributing authors argue that publicly-funded care homes remain critical to care arrangements but require policy and practice transformations to produce equitable and supportive conditions. Attentive to the specific contexts and tensions that shape care, chapters address key questions about care home quality and labour in relation to gender, race, ethnicity, religion and class. The book analyses the physical and social boundaries that set the conditions for quality of life and care, moving beyond the minimum to explain how nursing homes can provide joy. Offering alternative approaches to the complex challenges facing this vital public service, this book will be a key reference for students and scholars of health policy, comparative social policy and social work. Its integration of statistical, policy and practice analysis with ethnographic research will prove invaluable to those concerned with long-term care policy and practice"--

Abstract: Build a command-line tool with Apple's Swift language.

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

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

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

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

Abstract: Learn to build solutions with Go and the AWS Cloud9 environment via the AWS SDK

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

Abstract: Learn to use AWS Data Governance and Auditing Tools.

Abstract: Perform Data Science on Day One! 00:00 Intro 02:02 Data Science Project Structure Overview 05:15 Create Github Repo 07:28 Launch Github Codespaces 11:34 Using Colab Notebook 12:47 Using TOC in Colab Notebook 14:43 Saving notebook to Colab to Github 19:52 Ingesting CSV files into Colab 22:31 Describing Data using df.describe() 24:30 Plotting data with seaboard 28:30 lmplot 29:30 Comparing cumulative deaths in Covid19 plot by state 32:40 Merging Pandas Dataframe with election and Sugar Consumption 37:38 Exporting CSV file and uploading to Github from Colab result 39:27 Continuous Integration of Jupyter Notebook with Github Actions 40:44 Create Makefile 44:32 Using Github Actions to test Jupyter via nbval plugin 45:43 Using Github Status Badge for Jupyter Notebook test run pass

Abstract: "Adopting an interdisciplinary approach this book provides a cutting-edge, in-depth account of social policy research today, how we got here, and where future research should be headed. It defines the core research agenda for the future covering multiple social policy fields, including care, family, health, and housing policy as well as gender equality, labour market policy, and welfare attitudes. The book brings together a unique combination of scholars from social policy, sociology, political science, international relations, and law, who explore how European societies have changed over the last 20 years, the future challenges which need to be addressed and the role for social policy research. The editors argue that to advance research on European social policy, we need to develop a better understanding of the interplay between multiple policies, invest more resources in theoretical development, and effectively utilize perhaps the greatest asset of European social policy research - its multidisciplinarity. Offering crucial insights into the dynamic nature of social policy research, this book will be a valuable guide for social policy scholars and students. Its discussion of a broad range of social policy areas will also be useful for practitioners and policymakers across a wide range of social policy fields"--

Abstract: "This is an open access title available under the terms of a CC BY-NC-ND 4.0 License. It is free to read, download and share on Elgaronline thanks to generous funding support from The Swedish Governmental Agency For Innovation Systems, Vinnova. This timely book expertly examines ongoing pressing issues in the modern world namely, an unstable economic climate, political turmoil and the environmental crisis. It takes a unique look at how science, technology and innovation could contribute towards the creation of a smarter and more resilient society by allowing more inclusive approaches into how science is integrated. With an insightful global interdisciplinary approach, Smart Policies for Societies in Transition combines in-depth theoretical analysis whilst also providing a reflective look at broadening the scope of science and innovation policy in order to understand the critical issues and challenges. Chapters illustrate historical practices and events, and discuss how the move to smart politics and the linking of boundaries from a social, ecological and global viewpoint leads to fewer but more creative policies. With its retrospective and forward-thinking perspectives, this book will be an excellent resource for academics wanting to rethink their approach to science and innovation governance, whilst scholars will find the collaborative method for combining policy analysis with theory of policymaking and governance informative and illuminating"--

Abstract: "Elgar Research Agendas outline the future of research in a given area. Leading scholars are given the space to explore their subject in provocative ways, and map out the potential directions of travel. They are relevant but also visionary. This timely Research Agenda explores and proposes critical lines of research to support understanding of the conditions under which urban tourism contributes to the development of urban systems, and what can be done to create and conserve these conditions. Chapters highlight conceptual discussions, concrete case studies and policy reviews to address the issues surrounding the economic, environmental and social impacts of tourism on cities. Analysing the trends that have characterized urban tourism in the past, the Research Agenda looks ahead to those that may influence it in the future, including the impact of Covid-19. Chapters further offer a thorough conceptualization and innovative definitions of the phenomenon of urban tourism. The critical issue of the sustainability of tourism development in cities is also discussed in depth. The Research Agenda provides a comprehensive and up-to-date overview of the urban tourism debate, making it a critical read for urban studies and tourism scholars. The detailed case studies from across four continents will also be beneficial to policymakers and urban planners dealing with tourism development"--

Abstract: Step up your local setup by setting a remote compute instance with attached SMB storage and then connect your local VSCode editor so that you can execute code and Jupyter Notebooks remotely. In this video I go through everything you need to know to crete a compute instance in Azure, both in Azure Machine Learning Studio and using the Data Science Virtual Machine spot instance that allows you to save costs when running a high memory with GPU instance. Because remote compute instances in the cloud should be considered ephemeral, specially if you are using spot instances, this video also covers setting up a storage account and a file share configuration for a Samba share that allows you to attach that same storage to any compute. Topics include: Create an Azure compute instance Learn about Spot Instances and other cost savings Setup VSCode for remote code execution Create an SMB file share and attach it to a VM Execute Jupyter Notebooks remotely Useful links: * Github Repository with summary instructions * Create a File share documentation on Azure * Data Science VMs in Azure

Abstract: Setup quick and easy way to mount a SAMBA (SMB) file share in an Azure VM with a pre-configured BASH script. The shell script will allow you to automatically mount the share and save your work. This type of workflow allows your infrastructures and virtual machines to be resilient to failure. This is a short video that covers only setting up SMB on a VM. For a full video with setting up the VM, SSH access, and connect a remote compute to VSCode go here Follow along with more examples in the Github repository This video covers: Create a Storage Account Create a File Share for a Storage Account Use SSH to connect to a remote Virtual Machine Use a pre-configured shell script to mount the share Verify files and directories through the Azure portal 00:00 Introduction 00:26 Azure Portal Virtual Machines 01:00 SSH Connection string 01:41 Create a Storage Account in Azure 03:18 Create a File Share (SAMBA) in Azure 04:12 SAMBA connection snippet in BASH (Shell script) for mounting 05:06 Create the script in the Virtual Machine 05:34 Mount the SAMBA share and verify it is mounted in /mnt/ 06:45 Verify created files are available in the Azure Portal for the File Share Useful links: * Github Repository with summary instructions * Create a File share documentation on Azure * Data Science VMs in Azure

Abstract: Learn to deploy an AWS Lambda Function in Python with CDK. 00:00 Intro 00:36 Verify CDK Version 01:00 Initialize Python CDK app 02:09 Create AWS Python Lambda 02:50 Add AWS CDK Stack for AWS Lambda 03:42 Run cdk diff 04:06 bootstrap cdk 05:31 run cdk deploy result 06:01 test AWS Lambda in Console

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 K-Means clustering from theory to implementation 00:00 Intro 00:47 Theory of Machine Learning 05:00 Colab Notebook exploration of K-Means Algorithm 06:00 Distance Metrics 08:00 Creating K-Means Pipeline 12:00 Elbow Plots 14:00 Silhouette Plots 17:00 Running K-Means Serial Simulation 18:34 Running K-Means Parallel Simulation 20:00 Spinning up Huge Cloud9 128 GB Ram 32 vCPU Instance 23:00 Running massively parallel K-Means.

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: Learn to provision EC2 instances from both the AWS Console and AWS CloudShell. Also learn the key components of EC2 instance provisioning. 00:00 Intro 00:45 EC2 Instance Provisioning Key Component Diagram Walkthrough 03:18 Launching an EC2 Instance from AWS Console 04:06 Creating SSH key pair 04:46 Configuring Security Group rules 05:21 Walkthrough of Advanced Setting including User Data 06:33 Observing EC2 Instance State in Console 07:07 Using AWS CloudShell to launch and controll EC2 Instances 07:44 Finding AMI IDs to launch EC2 Instances from AMI Catalog 08:00 Launching EC2 Instances from AMI Catalog with AWS CloudShell 08:52 Connecting to EC2 Instances from AWS Console and logging into Linux shell 09:40 Walkthrough of EC2 Instance Connection options for Windows with RDP 10:56 Terminating Instances with AWS CloudShell and Bash AWS CLI 11:50 Recap of EC2 Instance Provisioning.

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 Hugo a popular Go-based content management system to deploy global-scale websites on AWS. 00:00 Intro 00:53 The need to spread information that helps humans at scale 02:26 Hugo Continuous Delivery with AWS CodeBuild workflow diagram 06:04 AWS CodeBuild 06:38 AWS Cloud9 07:56 Download Hugo and run it locally 09:40 Follow Hugo's Quickstart guide 11:36 Edit inbound rules for Cloud9 to preview running Hugo website 13:10 Looking at the buildspec.yml file for continuous delivery of Hugo website with AWS S3 and Cloudfront and Route 53 14:52 Walkthrough of AWS S3 static hosting 15:45 Walkthrough of AWS CodeBuild continuous delivery for Hugo console settings.

Abstract: Learn to master the Databricks platform for doing MLOps.

Abstract: Learn Key Skills in Software Engineering Craftmanship Course An Ongoing Course This video will show you how to use CUDA GPUs with Python. Lessons Covered Include: Introduction to course What is a Makefile and how do you use it? Popular Linux commands Configuring ~/.bashrc Using grep, cut, sort and uniq Introducing GitHub Codespaces Compiling Python in Github CodeSpaces What is DevOps and how do you use it? Kaizen Methodology Learn Continuous Integration Learn key software engineering principles and best practices for building software. Learn both concepts and hands-on techniques for building software. Learn software craftsmanship. 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 Rust Learning Rust by Live Coding This video series live codes Rust and iteratively learns the language. Lessons Covered Include: 1.0 52 weeks rust ep 1 getting started setup env 2.0 52 weeks rust ep 2 starting scripts 3.0 52 weeks rust ep 3 functions 4.0 52 weeks rust ep 4 loops 5.0 52 weeks rust ep 5 ownership more looping Learning Objectives Learn Rust 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: 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: Doing Hugging Face Building Solutions with Hugging Face This video course will show you how to build solutions with Hugging Face. Topics Covered Include: 1.0 Introduction to Course 1.1 Learn to use MLOPs methodology to deploy a Hugging Face Spaces application using Github Actions. Learning Objectives Build applications with Hugging Face Apply MLOPs methodology to deploy a Hugging Face Spaces application using Github Actions. 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 WT.mc_id=academic-0000-alfredodeza) Practical MLOps book Python for DevOps-Playlist.

Abstract: Assimilate AWS with Python Master AWS by Coding with Python in this ongoing series This video series covers mastering AWS in Python from the absolute beginning with incremental weekly lessons. Follow along for a deep dive into programmatically mastering AWS with Python. 1.0 Assimilate AWS by using Github Copilot and Github Codespaces to build solutions for S3, Apigateway and Click. 2.0 refactor boto3 code build translation click tool Assimilate AWS By Coding 3.0 Assimilate AWS By Coding EP3 Bash CloudEnvs Containers: Use Bash to build CloudEnvs and Containers Topics Covered Include: Python Basics Github Repo for Assimilate AWS 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: 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 PyTorch Learning PyTorch During Live Coding This video series covers live coding the PyTorch Language iteratively while learning the language. Lessons Covered Include: 1.0 Getting started with PyTorch in GitHub Codespaces with GPU (Live Coding) Learning Objectives Learn PyTorch Learning to build solutions with PyTorch Learning the key syntax and features of the PyTorch Framework 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: Assimilate C++ Learning C++ During Live Coding This video series covers live coding the Language iteratively thus learning the language. Lessons Covered Include: 1.0 github codespaces cpp hello world calculator Learning Objectives Learn C++ by live coding Learning to build solutions with C++ Learning the key syntax and features of the C++ 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 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: Demo of FastAPI + AWS App Runner

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

Abstract: Find out how to share and use Google Colab notebooks for data science!

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

Abstract: Learn to build out Continuous Integration with Github Actions and all clouds. Azure, AWS, GCP and Github Codespaces in Python.

Abstract: Learn to build a project from zero, test it with Github Actions. Next, build both Click and Fire Command-Line Tools. Finally containerize a Fast API Wikipedia Scraper and deploy to AWS App Runner. 00:00 Intro 03:00 Statements in Python using Colab 10:00 List and Dictionaries Python 21:00 Using Github Codespaces to build project 38:00 Setup Github Actions 44:00 Python Functions 1:03:00 Build Wikipedia bot 1:12:00 Build Click Command-Line Tool Interface Wikipedia Bot 1:38:15 Build Python Fire Command-Line Tool 1:42:21 Build FastAPI Wikipedia Bot 1:56:00 Containerize FastAPI Wikipedia Bot with Docker 2:07:08 Deploy AWS App Runner FastAPI Wikipedia Bot with Docker.

Abstract: Learn Python in five Minutes with Colab Notebook. Covers statements, lists, dictionaries, and for loops. 00:00 Intro 00:25 Using Colab 00:40 Tables of Contents in Colab 00:55 Save copy in Github 01:05 Print hello world 01:24 print equation 01:50 Using f-strings to print 02:05 using list data structures 02:20 Appending to a list 02:45 Looping with for loops in Python 03:30 Pushing to a list 04:00 Random Pushing to a container 05:19 Using a dictionary in Python.

Abstract: Swift Classes and Structures 00:00 Intro.

Abstract: Learn to build real-world Python Microservices that enable Continuous Delivery. 00:00 Intro 05:00 Scaffolding a project in Python 08:00 Setup Virtualenv 13:10 Building Makefile 24:00 Setup Github Actions 29:00 Formatting code with Python Black 45:09 Test code with Pytest and Pytest Coverage 50:30 Using Python Fire to build CLI 59:30 Write Wikipedia scraper 1:02:00 Use IPython to interact and debug code in Github Codespaces 1:08:00 Pinning FastAPI version number 1:12:00 Building FastAPI Microservice 1:18:00 Using Text blob NLP service to parse phrases 1:29:00 Debugging broken code 1:34:00 Building container 1:54:00 Setup AWS Code Build push to ECR (Elastic Container Registry) 2:02:00 Setup AWS Code Build to ECR to AWS App Runner Continuous Delivery View the code on Github here: https://github.com/noahgift/python-for-devops-april-2022.

Abstract: Learn to setup Mac M1 with Tensorflow and Metal 00:00 Intro 01:17 Install Conda and tensorflow-metal 02:02 Run Juypter Notebook 02:10 Train a model using Tensorflow and M1 GPU 02:34 Verify GPU is saturated 03:25 Verify Activity Monitor shows GPU and CPU history for Python 3.9.

Abstract: Learn to pass the AWS ML Certification Part 2 00:00 Intro 01:56 Artificial intelligence, machine learning, and deep learning. 02:34 Artificial Intelligence 03:10 Machine Learning 03:58 Deep learning 05:11 ML and technology advancements 06:00 Common ML Use Cases 08:14 Types of machine learning 09:21 Supervized learning 10:17 Computer vision 11:08 Unsupervized learning 12:44 Natural language processing 13:20 Reinforcement learning 14:34 Self-driving vehicles 15:04 When to use machine learning 15:35 ML pipeline: Business 16:23 ML pipeline: Data preparation 17:22 ML pipeline: Iterative model training 18:01 ML pipeline: Feature Engineering 19:25 ML pipeline: Model Training 20:18 ML pipeline: Evaluating and tuning the model 21:00 Overfitting and underfitting 22:48 Python tools and libraries 24:57 ML Frameworks 25:50 Amazon SageMaker 26:42 Machine learning managed services 28:30 Machine learning challenges.

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: Cutting Edge MLOps from Zero with Hugging Face and OpenAI Learn by doing This video course takes you from zero all the way to building solutions using MLOps. First the theory of MLOps is explained, then you will learn how to build a MLOps style solution from scratch using Hugging Face and OpenAI. You will also learn to use AI tools like Github Copilot, Hugging Face Spaces, and OpenAI Codex. Learning Objectives Learn to use Github Codespaces and customize your environment with devcontainer.json Learn the foundations of MLOps Explore new topics in the upcoming book Enterprise MLOps by O'Reilly Learn to use Github Actions to test AI projects Learn to use Github Copilot to write code for both Hugging Face and OpenAI Learn to build AI solutions using GPT-3 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: DevOps Theory to Practice Go from theory to implementation in this DevOps course with Python and AWS This video course will show you how to start your first day as a DevOps Engineer and progress. Topics Covered Include: DevOps Theory Learn useful Python skills for DevOps including working with the filesystem and processes. Build an AWS Boto3 tool with Python Fire for translation and test it with CI/CD. Build a containerized FastAPI service deployed to AWS App Runner through continuous delivery. Learning Objectives Learn the theory behind DevOps Walk through the implementation of several O'Reilly books including Python for DevOps, AWS for C# and Enterprise MLOps. Build an AWS Translation Service tool with Python and Boto3 Deploy a Pandas FastAPI web service with Python and FastAPI and AWS App Runner Build and use AWS CodeBuild with 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 .NET Learning .NET and C# by Live Coding This video series live coding .NET and iteratively learning the language. Lessons Covered Include: 1.0 52 Weeks of Live Coding NET Episode 1 codespaces.mp4 2.0 52 Weeks of Live Coding NET Episode 2 Xunit.mp4 3.0 52 Weeks of Live Coding NET Episode 3 Blazor.mp4 4.0 52 Weeks of Live Coding NET Episode 4 failing to get cdk1 working.mp4 5.0 52 Weeks of Live Coding NET Episode 5 success cdk2.mp4 Learning Objectives Learn .NET and C# and F# 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: 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: Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Build solutions use the entire GitHub Ecosystem This video series covers all major components of the GitHub Ecosystem. It is a great way to learn how to use GitHub for your projects. Lessons Include: 1.1 Key Concepts GitHub Ecosytem 1.2 demo GitHub Repo with teaching template 1.3 demo codespaces 1.4 demo gpu whisper 1.5 demo gpu hugging face fine tuning 1.6 demo copilot 1.7 demo github actions 2.0 building devops projects with GitHub ecosystem and copilot 3.0 building logistics projects withGitHub ecosystem and copilot Topics Covered Include: Multi-hour project walkthroughs Deploying AWS Microservices Using Github Actions Using Copilot to enable productive AI Pair Programming 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.