LLMs for Code Understanding, Refactoring, and Documentation Training Course
The LLMs for Code Understanding, Refactoring, and Documentation is a technical course designed to leverage large language models (LLMs) to enhance code quality, reduce technical debt, and automate documentation tasks across software teams in the public sector.
This instructor-led, live training (available online or onsite) is targeted at intermediate to advanced-level software professionals who seek to utilize LLMs such as GPT to analyze, refactor, and document complex or legacy codebases more effectively for government applications.
By the end of this training, participants will be able to:
- Use LLMs to explain code, dependencies, and logic in unfamiliar repositories.
- Identify and refactor anti-patterns to improve code readability.
- Automatically generate and maintain inline comments, README files, and API documentation.
- Integrate LLM-driven insights into existing continuous integration/continuous deployment (CI/CD) and review workflows for government projects.
Format of the Course
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course tailored to specific government needs, please contact us to arrange.
Course Outline
Understanding Code with LLMs
- Prompting strategies for code explanation and walkthroughs
- Working with unfamiliar codebases and projects
- Analyzing control flow, dependencies, and architecture
Refactoring Code for Maintainability
- Identifying code smells, dead code, and anti-patterns
- Restructuring functions and modules for clarity
- Using LLMs for suggesting naming conventions and design improvements
Improving Performance and Reliability
- Detecting inefficiencies and security risks with AI assistance
- Suggesting more efficient algorithms or libraries
- Refactoring I/O operations, database queries, and API calls
Automating Code Documentation for Government
- Generating function/method-level comments and summaries
- Writing and updating README files from codebases
- Creating Swagger/OpenAPI docs with LLM support
Integration with Toolchains for Government
- Using VS Code extensions and Copilot Labs for documentation
- Incorporating GPT or Claude in Git pre-commit hooks
- CI pipeline integration for documentation and linting
Working with Legacy and Multi-Language Codebases for Government
- Reverse-engineering older or undocumented systems
- Cross-language refactoring (e.g., from Python to TypeScript)
- Case studies and pair-AI programming demos
Ethics, Quality Assurance, and Review for Government
- Validating AI-generated changes and avoiding hallucinations
- Peer review best practices when using LLMs
- Ensuring reproducibility and compliance with coding standards
Summary and Next Steps for Government
Requirements
- Experience with programming languages such as Python, Java, or JavaScript for government projects
- Familiarity with software architecture and code review processes in a public sector context
- Basic understanding of how large language models function within governmental applications
Audience
- Backend engineers working on federal initiatives
- DevOps teams supporting government agencies
- Senior developers and tech leads in the public sector
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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Testimonials (1)
Lecturer's knowledge in advanced usage of copilot & Sufficient and efficient practical session
Tan - ViTrox Technologies Sdn Bhd
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