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Duration 14 hours
Course Outline
Gaining Code Insight through LLMs
- Developing prompting strategies for code explanation and walkthroughs.
- Navigating unfamiliar codebases and project structures.
- Analyzing control flow, inter-module dependencies, and system architecture.
Refactoring for Long-Term Maintainability
- Recognizing code smells, obsolete code, and anti-patterns.
- Restructuring functions and modules to enhance clarity.
- Utilizing LLMs to propose naming conventions and architectural improvements.
Enhancing Performance and Reliability
- Identifying inefficiencies and security vulnerabilities with AI assistance.
- Recommending more efficient algorithms or library alternatives.
- Optimizing I/O operations, database queries, and API interactions.
Streamlining Code Documentation
- Generating function-level comments and method summaries.
- Drafting and updating README files directly from codebases.
- Producing Swagger/OpenAPI documentation with LLM support.
Integration with Development Toolchains
- Leveraging VS Code extensions and Copilot Labs for documentation tasks.
- Incorporating GPT or Claude into Git pre-commit hooks.
- Embedding LLM checks into CI pipelines for documentation consistency and linting.
Managing Legacy and Multi-Language Systems
- Reverse-engineering older or undocumented systems.
- Executing cross-language refactoring tasks (e.g., migrating from Python to TypeScript).
- Examining case studies and pair-AI programming demonstrations.
Ethics, Quality Assurance, and Review Protocols
- Validating AI-generated changes and mitigating the risk of hallucinations.
- Applying best practices for peer review when LLMs are involved.
- Ensuring reproducibility and adherence to coding standards.
Conclusion and Path Forward
Requirements
- Proficiency in programming languages such as Python, Java, or JavaScript.
- Working knowledge of software architecture principles and code review methodologies.
- A fundamental grasp of the operational mechanisms of large language models.
Target Audience
- Backend Engineers
- DevOps Teams
- Senior Developers and Technical Leads
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
