Copilot GenAI course in work – automation and support

Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

Effective Copilot use - You will learn how to use GitHub Copilot in VS Code, Visual Studio, and JetBrains to write code faster, reduce manual boilerplate work, and make better use of your project context.

Better coding prompts - You will master prompts for generating functions, classes, APIs, and components, so you can get more accurate outputs, spend less time on fixes, and work with AI more predictably.

Faster code generation - You will learn how to use AI to build new modules, endpoints, data structures, and frontend elements, helping you shorten implementation time and deliver working features sooner.

AI-assisted refactoring - You will learn to analyze existing code, spot anti-patterns, and simplify complex sections, so you can improve readability, modernize legacy solutions, and evolve projects with more confidence.

Testing and debugging - You will practice generating unit and integration tests, reviewing coverage, and diagnosing issues from logs and exceptions, so you can find problems faster and raise code quality.

Automated documentation - You will see how to create comments, API docs, README files, and architecture descriptions with AI support, making it easier to prepare team materials and speed up developer onboarding.

Working with AI agents - You will explore Copilot Chat, Agent Mode, and full repository context, allowing you to plan broader changes, handle multi-step tasks, and split work between yourself and AI in a practical way.

AI in DevOps and review - You will learn how to use AI for commit messages, Pull Request descriptions, change summaries, and code review support, improving team collaboration and keeping code aligned with standards.

Training programme

1. Introduction to AI supporting programming

the role of generative AI in the software development process:
- the evolution of tools supporting programmers,
- capabilities and limitations of language models,
- GitHub Copilot, ChatGPT, Claude and Gemini in a programmer's work,
- security and legal aspects of using AI,
overview of the GitHub Copilot environment:
- versions and functionalities of GitHub Copilot,
- integration with Visual Studio Code, Visual Studio and JetBrains,
- configuration of the work environment,
- discussion of Copilot work modes.

2. Effective Prompting for Developers

creating effective commands:
- how to describe functional requirements,
- formulating prompts for code generation,
- using project context,
- iterative refinement of responses,
techniques for working with AI:
- Prompt chaining,
- Few-shot prompting,
- role prompting,
- generating code compliant with organizational standards.

3. Code generation using GitHub Copilot

creating new functions and components:
- generating methods and classes,
- creating APIs and endpoints,
- generating frontend components,
- automatic creation of data structures,
practical use of Copilot:
- real-time code completion,
- generating boilerplate code,
- creating code documentation,
- speeding up daily programming tasks.

4. Refactoring and improving code quality

analysis of existing code:
- identification of quality issues,
- detection of anti-patterns,
- improving code readability,
automatic refactoring:
- simplifying complex fragments,
- modernization of legacy code,
- performance optimization,
- migration between framework and library versions.

5. AI-assisted testing

test generation:
- creating unit tests,
- generating integration tests,
- building test cases,
- Test coverage analysis,
error detection:
- analysis of exceptions and logs,
- diagnostics of problems in applications,
- using AI for debugging,
- searching for potential vulnerabilities.

6. Technical documentation and code analysis

automatic creation of documentation:
- generation of comments and API documentation,
- creation of README and deployment instructions,
- documentation of application architecture,
analysis of large codebases:
- understanding a foreign project,
- dependency analysis,
- creation of summaries of modules and classes,
- supporting the onboarding of new developers.

7. Programming using AI agents

modern GitHub Copilot features:
- Copilot Chat,
- Agent Mode,
- Workspace Context,
- integration with GitHub repositories,
execution of complex tasks:
- planning changes in the project,
- implementation of multi-stage functionalities,
- automation of repetitive programming tasks,
- human–AI collaboration in software development.

8. AI in the DevOps and Code Review process

support for the software development process:
- generating commit messages,
- creating Pull Requests,
- automatic summaries of changes,
AI in code review:
- code quality analysis,
- improvement suggestions,
- verification of compliance with standards,
- supporting the code review process.

9. Project workshop

implementation of a sample project using AI:
- requirements analysis,
- generation of the solution architecture,
- implementation of functionalities,
- creation of testów,
- refactoring and optimization,
- preparation of documentation.

10. Best practices for working with GitHub Copilot and GenAI

organization of the work of a developer supported by AI:
- when to trust AI and when to verify responses,
- quality control of generated code,
- protection of source code and company data,
- building your own prompt libraries,
summary and development directions:
- the latest AI trends for developers,
- agentic development environments,
- AI-native software development,
- plan for further competency development.

What are the prerequisites for participating in the training?

Programming basics - You should be comfortable reading and writing code in at least one programming language, so you can assess AI suggestions, refine them, and use them in real development tasks.

IDE and Git workflow - You should know the basics of working in an IDE and using Git, since the training covers Copilot inside development tools and practical work with code in a repository.

Testing and debugging knowledge - You should understand unit tests, runtime errors, and application logs, so you can use AI effectively for test generation, troubleshooting, and issue analysis.

Project experience - You should have experience working on a software project, so you can better use code context, analyze architecture, and plan changes with the support of AI tools.