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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

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