Abstract: Automated deletion of Azure Resources Prevent surprise bills with automation Prevent your Azure bill from running wild! In this video I show how you can automate the removal of Azure resources on demand or by schedule. With GitHub Actions and an Azure account you can prevent services from running wild and causing unnecessary billing overcharges! With automation in place, there is no need to remember what VM you left running! First, you'll start by creating a GitHub Action that authenticates to Azure, then you will query locally your resource groups to identify which ones you can delete. Next, you will port the query over to the Action workflow. Finally, you will delete resources that match, making sure those are fully removed, preventing a large bill. You will need a GitHub and Azure account, an Azure Service Principal and the Azure CLI installed locally. Learning Objectives In this lesson you will learn: Create a GitHub Action workflow to query Resource Groups Query Resource Groups that match locally Use scripting to extract Resource Group names Remove Resource Groups with the Azure CLI in GitHub Actions Useful Resources Sample GitHub repository Create an Azure Service Principal for GitHub Actions Azure Service Principal documentation Install Azure CLI Free Azure Certification for Students Introduction to GitHub Actions Run Python In GitHub Actions.

Abstract: Intro to Pandas Over 1 hour of course material with practice code Quickly learn to use Pandas with examples Learn how to work with data using Pandas and NumPy. From loading and reading datasets from different sources to plotting graphs and exploring common problems in data. Pandas will allow you to perform transformations and export your data into different formats, and NumPy will boost your ability to work with numerical data. This course is meant for beginners that want to understand Pandas from the start and find more about NumPy. All lessons and videos have accompanying GitHub Repositories with example code. Reference GitHub Repository Learning Objectives In this course you will learn to: Load and export data from different sources Manipulate data in datasets Apply functions and transform columns Query for specific data Perform common operations on NumPy arrays Resources Python for beginners course Python Functions and Classes course Python Dictionaries course Introduction to Testing in Python course Pytest Master Class Python Bootcamp for Data Practical MLOps 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: Rust Bootcamp Course Overview Welcome to our comprehensive Rust programming course! In this immersive learning experience, we will guide you through every aspect of Rust, empowering you to become a proficient developer. This course is ideal for beginners wanting to become proficient in Rust or from existing developers coming from languages like Python or JavaScript that want to learn Rust fundamentals. Get started by setting up your preferred text editor and installing Rust. We'll ensure that you have all the necessary tools to create a productive coding environment. By leveraging the capabilities of Visual Studio Code and enabling the Rust Analyzer, you'll unlock a feature-rich ecosystem that enhances your development workflow. Experience the game-changing potential of GitHub Copilot, an AI-powered assistant. Sign up for GitHub Copilot and witness its transformative impact on your coding experience. We'll guide you through the installation process and show you how to leverage its intelligent suggestions for accelerated programming. Master concepts and fundamentals like control flow, variable assignment, and immutability. Learn the intricacies of loops, conditional statements, and effective error handling techniques. With Rust's borrowing concept at your disposal, you'll develop secure and high-performance code. Build upon your foundation with advanced topics like structs, string manipulation, and working with vectors and enums. We'll explore real-world library development using Cargo, Rust's robust package manager. Effective documentation and debugging techniques will become second nature as you optimize your code. Organize your code effectively with modules, extending functionality and enhancing reusability. Dive into comprehensive testing methodologies to ensure the reliability and correctness of your programs. From writing tests for your code to handling private components, you'll gain expertise in developing robust software projects. Our immersive learning experience includes hands-on examples, interactive exercises, and practical projects. Rust's performance, safety, and expressiveness will be at your fingertips as you embrace its immense potential. Join us on this rewarding journey to unlock the power of Rust programming and propel your career forward. Enroll now and gain the skills, knowledge, and expertise to thrive in the world of Rust. Whether you're a beginner, coding novice, or an experienced developer seeking new horizons, our course is your gateway to writing elegant, reliable, and high-performance code. Embrace the possibilities of Rust and embark on a rewarding programming journey today with one of the most loved programming languages. Learning Objectives Gain a solid understanding of Rust's core concepts, including variable assignment, control flow, and immutability, to write efficient and reliable code. Master the utilization of powerful development tools such as Visual Studio Code and the Rust Analyzer, enhancing productivity and enabling seamless coding experiences. Explore GitHub Copilot and learn how to leverage its AI-driven suggestions to accelerate programming and boost code quality. Develop proficiency in working with advanced Rust features, such as structs, enums, and string manipulation, to build robust and flexible applications. Discover the intricacies of module organization and extend functionality through effective code structuring, promoting code reusability and maintainability. Acquire comprehensive testing skills, including writing tests for code components and handling private code, ensuring the reliability and correctness of Rust programs. Gain hands-on experience in real-world library development using Cargo, Rust's package manager, and become proficient in documenting code and debugging techniques. These compelling learning objectives will guide you through the course, helping you acquire essential skills and knowledge to become a confident Rust developer. Course Content This course is divided into 4 weeks with 3 lessons that contain about 6 videos each. Each video is about 5 minutes long and contains a hands-on demonstration of the concepts covered in the lesson. The course is designed to be taken in order, but you can jump to any lesson you want to learn more about. Week 1: Setting up your development environment Reference GitHub Repository Setting up your text editor Using GitHub Copilot with Rust Introduction to GitHub Codespaces for Rust Week 2: Rust fundamentals Reference GitHub Repository Introduction to Rust Loops and Control flow Function basics Week 3: Structs, Types, and Enums Reference GitHub Repository Using structured data Exploring strings and vectors Working with Enum and Variants Week 4: Applying Rust Reference GitHub Repository Building a real-world library Extending functionality with modules Testing Rust code About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to build with the Rust programming language. Resources Deploy Rust on Azure Functions DevOps command-line tools in Python and Rust Switching to Rust from Python First Steps with Rust Learning Path.

Abstract: Hugging Face for MLOps Learn how to leverage Hugging Face and its powerful machine learning capabilities. Build, train, and deploy your own models using the Hugging Face platform and libraries. In this course you'll get hands-on with Hugging Face and learn how to: Access and use pre-trained models from the Hub Fine-tune models with your own data Build machine learning pipelines with Hugging Face Transformers Add and version your own datasets Containerize and deploy Hugging Face models Automate workflows with GitHub Actions By the end, you'll have practical experience building, training, and deploying Hugging Face models, including production deployment to the Azure cloud. Learning objectives Find and use pre-trained models Fine-tune models for custom tasks Build ML pipelines with Hugging Face libraries Create and version datasets Containerize models for production Automate workflows for MLOps Lesson 1: Getting Started with Hugging Face Lesson Outline Overview of Hugging Face Hub Browsing models and datasets Using Hugging Face repositories Managing spaces and access Lesson 2: Applying Hugging Face Models Lesson Outline Downloading models from the Hub Using models with PyTorch/TensorFlow Leveraging tokenizers and pipelines Performing inference with Hub models Lesson 3: Working with Datasets Lesson Outline Browsing datasets on Hugging Face Uploading and managing datasets Versioning datasets with dataset cards Loading datasets in PyTorch/TensorFlow Lesson 4: Model Serving and Deployment Lesson Outline Containerizing Hugging Face models Creating inference APIs with FastAPI Deploying to cloud services like Azure Automating with GitHub Actions About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience teaching and authoring content about LOps will give you everything you need to get started applying these powerful concepts. Resources MLOps with Databricks Introduction to MLflow for MLOps Hands-on Python for MLOps.

Abstract: Rust For DevOps Learn how to use and apply DevOps principles using Rust This is an early release of the course. In this course, you will learn the basics of DevOps using the Rust programming language. DevOps helps you build, test, and deploy code faster while creating a robust foundation for your projects and teams. First, we will talk about what DevOps is. You will learn things like automation, monitoring, and working together as a team. Then, we will see how to use DevOps ideas in Rust code. You will learn about version control, testing, containers, and deploying Rust programs. Although this course explains the foundations of DevOps and using Rust which is ideal for beginners, experienced Rust developers will find solid advice in how to apply DevOps best practices to existing applications. Learning Objectives The core principles and practices of DevOps How to apply DevOps concepts to build, package, and deploy applications with Rust The basics of containerization and how to leverage containers for DevOps with Rust Course Content This course is divided into 4 weeks with 3 lessons that contain about 6 videos each. Each video is about 5 minutes long and contains a hands-on demonstration of the concepts covered in the lesson. The course is designed to be taken in order, but you can jump to any lesson you want to learn more about. Week 1: Introduction to DevOps Principles Introduction to DevOps Principles DevOps Considerations for Applications Basics of Containerization Week 2: Implementing monitoring and logging strategies Introduction to monitoring and logging strategies Tools and Services for monitoring and logging Logging with Rust About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to build robust applications and infrastructure with the Rust programming language and for Rust applications. Resources Rust Bootcamp Deploy Rust on Azure Functions DevOps command-line tools in Python and Rust Switching to Rust from Python First Steps with Rust Learning Path.

Abstract: VSCode development environments Learn different options for programming with VSCode Find out different ways you can use VSCode for development: on the web, with Codespaces or locally with configurable Docker containers This video will cover what makes each one different and when you might want to use one vs. the other. From quick edits on GitHub to a more powerful machine backed by a remote compute using Codespaces, it is all about flexibility! Topics Covered Include: Use quick edits with GitHub.dev that show on your repository Open any repository with VSCode.dev Use Codespaces with a powerful remote compute Configure a local codespace with Devcontainers using Docker Additional 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.

Abstract: MLOps deployment to Azure Container Apps Take advantage of insta-scaling for live inferencing Learn how to deploy an ML container with FastAPI and deploy it to Azure Container Apps with GitHub Actions. This repository gives you a good starting point with a Dockerfile, GitHub Actions workflow, and Python code that already works for generating text using GPT-2 with HuggingFace Transformers. First, you'll go through an architectural overview of the end-result, then you will go through every configuration item needed to set the automation right between Azure and GitHub Actions and the GitHub Container Registry. Finally, you'll see how to deploy and find a few crucial requirements needed for everything to work, like ingress ports and setting the right amount of RAM and CPU. Learn Objectives In this video lesson, I'll go over the details with an example repository you can use for reference including the following learning objectives: Use GitHub Container Registry to push a built container Use the Azure CLI in a GItHub Action to authenticate to Azure How to generate an Azure Service Principal and a Personal Access Token to authenticate Configure Azure Container Apps to correctly serve a model with enough resources Look at deployment logs to ensure things are working right Resources Example repository Practical MLOps book MLOps Maturity Model Packaging ML models MLOps packaging: HuggingFace and Docker MLOps packaging: HuggingFace and Azure Container Registry.

Abstract: VSCode for the web Use VSCode directly on the web for editing Git repos Although you can use VSCode locally, using it in the web allows you to avoid having an install and dealing with platform problems. There is no account required and you can directly edit GitHub repositories on the web. In the case of Python, there are a couple of constraints that you must be aware of, like no support to run the terminal and execute a Python program. But syntax and intellisense works great, and we can even make Jupyter Notebooks work with the help of an extension. If you are a beginner and trying out different text editors, or even if you are a seasoned developer, you will find a case to use this feature of VSCode. Learning Objectives In this lesson you will learn: Opening a GitHub repository directly on the web and start editing it Commit and push changes from VSCode on the web to GitHub What are the constraints and limitations of the Python support Use Jupyter Notebooks and find what are some of the problems you may find Useful Resources VSCode for the Web documentation Minimal Python book Free Azure Certification for Students Develop web applications with Visual Studio Code.

Abstract: Introduction to Azure Functions Create a function with Python and Flask Learn how to create an Azure Function in the fastest way using instant deployment with Visual Studio Code, and then find out how to take it to the next level by using the Flask framework to take advantage of common Python patterns you might already be used to. Finally, we'll go through automation steps using GitHub Actions so that you can re-deploy your Azure Function after merging changes. This will give you confidence for deployment, make it less error-prone, and give you a foundational workflow to implement serverless technology using the Azure cloud. Learning Objectives Create an Azure Function using the Azure Portal Quickly build a function using Visual Studio Code Deploy in one click with the Azure Functions extension Modify your code and routes to use Flask Use GitHub Actions for automating the deployment process About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience creating courses with Codespaces is seen throughout this course, where you will get a first-hand experience with practical examples as well as applicable configuration for any development environment. Resources GitHub Codespaces course Microsoft Azure Fundamentals (AZ-900) Certification Pytest Master Class Practical MLOps book.