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Duration 14 hours
Course Outline
Comprehending Code via LLMs
- Strategies for prompting to facilitate code explanation and walkthroughs
- Navigating unfamiliar codebases and projects
- Analyzing control flow, dependencies, and system architecture
Refactoring Code for Enhanced Maintainability
- Identifying code smells, dead code, and anti-patterns
- Reorganizing functions and modules for improved clarity
- Utilizing LLMs to suggest naming conventions and design enhancements
Boosting Performance and Reliability
- Detecting inefficiencies and security risks with AI assistance
- Recommending more efficient algorithms or libraries
- Optimizing I/O operations, database queries, and API calls
Automating Code Documentation
- Generating function/method-level comments and summaries
- Drafting and updating README files based on codebases
- Creating Swagger/OpenAPI docs with LLM support
Integrating with Development Toolchains
- Utilizing VS Code extensions and Copilot Labs for documentation
- Embedding GPT or Claude in Git pre-commit hooks
- Integrating with CI pipelines for documentation and linting
Handling Legacy and Multi-Language Codebases
- Reverse-engineering older or undocumented systems
- Cross-language refactoring (e.g., migrating from 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 review when utilizing LLMs
- Ensuring reproducibility and adherence to coding standards
Summary and Next Steps
Requirements
- Proficiency in programming languages such as Python, Java, or JavaScript
- A solid grasp of software architecture and code review processes
- Fundamental knowledge of how large language models operate
Target Audience
- Backend engineers
- DevOps teams
- Senior developers and tech leads
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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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
