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?

More effective AI-assisted work - You will understand how GitHub Copilot supports everyday development work and how to use it for different tasks, so you can write, improve and review code faster with fewer avoidable mistakes.

A ready-to-use setup - You will configure Copilot in VS Code, Visual Studio or JetBrains IDEs, tailor it to your coding style and learn how to fix the most common startup and integration issues on your own.

Faster code creation - You will practice generating functions and classes from comments and learn how to write better prompts, so you can build solid solution drafts quickly and turn them into working code.

Tests and docs with less effort - You will use Copilot to generate unit tests, code comments and documentation, which will reduce maintenance time and make it easier to hand over changes to other people on your team.

Hands-on across languages - You will see practical Copilot examples in Python, JavaScript, TypeScript, C# and SQL, making it much easier to transfer the techniques to your own stack and everyday project work.

Better prompts and habits - You will learn prompt and comment patterns that lead to more accurate suggestions, helping you cut down on irrelevant completions and reach useful results with less trial and error.

Safer use of Copilot - You will learn when to trust AI suggestions and when to review them manually, while also taking licensing, code security and copyright-related risks into account in your daily work.

Practice on realistic tasks - Through short exercises and a micro-application build, you will work with Copilot on realistic tasks and review the generated code together to judge its quality and practical usefulness.

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 simple code in at least one programming language, so you can focus on using Copilot rather than catching up on core coding basics.

IDE familiarity - You should know how to work in an editor or IDE such as VS Code, Visual Studio or a JetBrains tool, so you can move smoothly through setup, configuration and hands-on exercises.

Git and GitHub basics - You should understand the basics of GitHub and know what an account, repository and service login are, because the training includes enabling and using Copilot in the GitHub ecosystem.

Reading code and tests - You should be able to review existing code and simple unit tests, so you can assess AI suggestions, spot mistakes and improve generated snippets during the practical exercises.