AI assistants have become a natural part of many developers' everyday work. They can speed up Python development, but they can also introduce vulnerabilities, incorrect dependencies, and insecure patterns that look convincing on first review.
In this course, you will learn how to use AI as development support in a controlled and secure manner. The course connects Python development with secure coding, verification of AI-generated code and specific security mechanisms for you who use tools such as GitHub Copilot, Cursor, Claude Code or similar. You will also get a basic introduction to some relevant concepts within ICT security.
The focus is not to replace the developer's professional judgment, but to make it stronger: better prompts, clearer requirements, more systematic testing, more secure handling of dependencies and secrets, and a workflow that makes it easier to trust the code before it is taken further.
What you will learn on the course
- Use AI assistants in Python development in a way that ensures security, privacy, and control over source code
- Recognize typical vulnerabilities in AI-generated Python code, including hard-coded secrets, vulnerable dependencies, and hallucinated packages
- Setting better requirements for AI tools through precise prompts, context documents and clear acceptance criteria
- Verify AI output with code review, tests, and automated security tools
- Setting up convenient security mechanisms including .gitignore, pre-commit hooks, and access control for remote connections
- Assess when AI-assisted development is appropriate, when the risk becomes too high, and how the risk can be communicated to teams and management
Course completion
The course is set up as a combination of short professional reviews, live demos, practical exercises and discussion. Participants work with realistic Python examples where AI is used as a development assistant, and learn to investigate, test, improve and assess when the code is safe enough to be used.
Emphasis is placed on a practical workflow that participants can bring back to their own working day: from the first prompt and context description, via development and code review, to testing, dependency control and handling of secrets.
