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Course Outline
Introduction to LLMs in Software Development
- Overview of LLMs and their role in code generation
- The evolution of automated coding tools
- Understanding the capabilities and limitations of LLMs for coding
LLMs for Automated Code Generation
- Setting up LLMs for code generation
- Best practices for writing prompts and interpreting LLM outputs
- Hands-on exercises with LLMs to generate code for common patterns
Enhancing Code Quality with LLMs
- Using LLMs for code review and bug fixing
- Integrating LLMs with version control systems
- Case studies on LLMs improving code efficiency
LLMs for Software Documentation
- Automating documentation generation with LLMs
- Ensuring consistency and completeness in documentation
- Customizing LLMs for different documentation styles and standards
Advanced Techniques in LLMs
- Fine-tuning LLMs for specific coding languages and frameworks
- Developing custom LLM models for unique project needs
- Exploring the latest advancements in LLM technology
Ethical and Legal Considerations
- Addressing the ethical implications of automated code generation
- Understanding the legal aspects of using LLM-generated code
- Best practices for responsible use of LLMs in software development
Project Work
- Implementing LLMs in a coding task
- Peer reviews and collaborative problem-solving sessions
Summary and Next Steps
Requirements
- An understanding of software development processes
- Experience with a programming language (e.g., Python, JavaScript)
- Familiarity with basic machine learning concepts
Audience
- Software developers
- Technical writers
- Project managers
14 Hours
