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Duration 14 hours
Course Outline
Introduction to LLMs in Software Development
- Overview of LLMs and their application in code generation.
- The progression of automated coding tools over time.
- Evaluating the strengths and constraints of LLMs in coding contexts.
Automated Code Generation with LLMs
- Configuration of LLMs for code generation tasks.
- Best practices for crafting prompts and interpreting LLM outputs.
- Practical exercises generating code for common patterns using LLMs.
Improving Code Quality via LLMs
- Applying LLMs for code review and error resolution.
- Integration of LLMs with version control systems.
- Case studies demonstrating how LLMs enhance code efficiency.
Software Documentation with LLMs
- Automating the generation of technical documentation.
- Maintaining consistency and completeness in written documentation.
- Adapting LLMs to fit various documentation styles and industry standards.
Advanced LLM Techniques
- Fine-tuning LLMs for specific programming languages and frameworks.
- Developing custom LLM models to address unique project requirements.
- Reviewing recent advancements in LLM technology.
Ethical and Legal Implications
- Analyzing the ethical dimensions of automated code generation.
- Understanding the legal framework surrounding LLM-generated code.
- Implementing best practices for responsible LLM usage in development.
Project Work
- Applying LLMs to a practical coding assignment.
- Conducting peer reviews and collaborative problem-solving sessions.
Conclusion and Future Directions
Requirements
- A solid grasp of standard software development processes.
- Proficiency in at least one programming language (e.g., Python, JavaScript).
- Basic familiarity with machine learning concepts.
Intended Audience
- Software developers.
- Technical writers.
- Project managers.
