Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Comprehending Code with LLMs
- Prompting techniques for code explanation and walkthroughs.
- Navigating unfamiliar codebases and projects.
- Analyzing control flow, dependencies, and architectural structures.
Refactoring for Maintainability
- Identifying code smells, dead code, and anti-patterns.
- Restructuring functions and modules for improved clarity.
- Utilizing LLMs to suggest naming conventions and design enhancements.
Enhancing Performance and Reliability
- Identifying inefficiencies and security vulnerabilities with AI assistance.
- Recommending more efficient algorithms or libraries.
- Refactoring I/O operations, database queries, and API calls.
Automating Code Documentation
- Generating function and method-level comments and summaries.
- Writing and updating README files directly from codebases.
- Creating Swagger/OpenAPI documentation with LLM support.
Toolchain Integration
- Leveraging VS Code extensions and Copilot Labs for documentation tasks.
- Incorporating GPT or Claude into Git pre-commit hooks.
- Integrating LLMs into CI pipelines for documentation and linting.
Managing Legacy and Multi-Language Codebases
- Reverse-engineering older or undocumented systems.
- Performing cross-language refactoring (e.g., converting Python to TypeScript).
- Case studies and pair-AI programming demonstrations.
Ethics, Quality Assurance, and Review
- Validating AI-generated changes and mitigating hallucinations.
- Best practices for peer reviews when using LLMs.
- Ensuring reproducibility and adherence to coding standards.
Summary and Next Steps
Requirements
- Proficiency in programming languages such as Python, Java, or JavaScript.
- Familiarity with software architecture and code review methodologies.
- Foundational knowledge of how large language models operate.
Audience
- Backend engineers
- DevOps teams
- Senior developers and technical leads
14 Hours
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