Deep dive into Artificial Intelligence to improve developer productivity
AI holds tremendous potential and moves ahead at breakneck speed. One of the areas in which it shines is helping you increase your productivity as a developer, in and out of Visual Studio. In this deep dive course, which starts where the related getting started course stopped, you’ll learn how to do that. The course is focused on GitHub Copilot, but other assistants and approaches are also covered. You’ll learn how to use it in a variety of IDEs. You’ll learn how it can help write tests, optimise code, commit code, review PRs, and even iteratively help you implement a user story with Copilot Edits. After that, a substantial part of the course is dedicated to evaluating LLMs: you’ll get a taste of Mistral Large, Claude Sonnet, GPT4o and others. A variety of LLMs is then used to teach you advanced prompt engineering techniques to improve the results you’ll get. The final section of the course is about extension and AI agents: you’ll learn how to write your own agent that integrates with GitHub Copilot.
Curriculum
Welcome (01:21)
What will you learn in this course? (02:27)
Who is the course for and prerequisites (01:14)
Introduction (00:40)
Positioning GitHub Copilot (04:12)
Setting Up GitHub Copilot in VS Code (01:45)
Working With GitHub Copilot in VS Code (09:46)
Setting Up GitHub Copilot in JetBrains Rider (02:13)
Working With GitHub Copilot in JetBrains Rider (04:10)
Working With GitHub Copilot in the GitHub CLI (07:20)
Working With GitHub Copilot in Other IDEs (01:32)
Section Recap (02:20)
Introduction (01:13)
Getting to Know the Demo Codebase (04:15)
Unit Tests, Integration Tests and End-to-End Tests (03:24)
Generating Dummy Data (13:58)
Generating and Running Unit Tests (10:52)
Generating and Running Integration Tests (15:43)
WebApplicationFactory: Integration Tests or End-to-End Tests? (03:51)
Generating and Running End-to-End Tests (08:03)
Generating Test Requests (01:27)
Section Recap (00:49)
Introduction (00:46)
Improving Your Codebase (09:23)
Working With Copilot Edits (07:58)
Section Recap (01:01)
Introduction (00:32)
Committing Code and Creating Pull Requests in Visual Studio (05:11)
Creating Pull Requests on GitHub (06:54)
Section Recap (01:04)
Introduction (00:42)
LLMs, From Generic to Specific (08:14)
How LLMs Are Rated (10:16)
Should You Be Running Benchmarks Yourself? (01:15)
Comparing Popular LLMs (05:45)
Evaluating ChatGPT (GPT4o) for Development (06:46)
Evaluating Mistral (Mistral Large) for Development (06:04)
Evaluating Claude (Sonnet) for Development (06:25)
Integrating Claude in Your IDE (06:41)
Evaluating Amazon Q Developer for Development (09:54)
Integrating With LLMs From Code (02:05)
Section Recap (02:37)
Introduction (00:37)
Prompts, Prompt Engineering and the Lingo Problem (04:41)
Manipulating LLM System Prompts (04:46)
Zero-, One-, and Few-shot Prompting (06:23)
Weighted Prompting (03:08)
Chain-of-Thought (CoT) Prompting (04:03)
Reasoning and Acting (ReAct) Prompting (04:39)
Retrieval-augmented Generation (RAG) Prompting (02:03)
Section Recap (03:23)
Introduction (01:18)
About AI Agents and Extensions (01:58)
Discovering Extensions (02:37)
Installing and Using an Extension (02:39)
Creating an AI Agent with Retrieval-augmented Generation (RAG) Prompting Support (04:28)
Creating a Custom AI Agent: Plumbing (15:26)
Creating a Custom AI Agent: Implementation (19:08)
Creating a Custom AI Agent: Tightening the Implementation (10:02)
Section Recap (01:41)
Course Info
Level:
Deep Dive
Duration:
4h 55m
Rating (New):
Lifetime access
Add to CartAbout the Author
Kevin Dockx
Kevin is a freelance solution architect, author & consultant, living in Antwerp (Belgium). He started working in the IT sector over 20 years ago, and is an 11-time Microsoft MVP. He's focused on architecture & security for web applications & integration components, using .NET and Azure. He's a keen proponent of open-source software. Also: wine.
More courses by Kevin Dockx© 2025 Dometrain. All rights reserved.