GenAI For Software Developers
Duration : 2 Days
Course Contents
Day 1: Introduction to Generative AI and GPT
Session 1: Understanding Generative AI
- What is Generative AI?
- Evolution of AI: From rule-based systems to Generative AI.
- Applications: Content creation, software development, data analysis.
- Core Concepts:
- Generative vs Discriminative Models.
- Neural Networks and Transformers.
Session 2: Introduction to LLMs and GPT
- What are Large Language Models (LLMs)?
- Training, data, and architecture.
- Examples: GPT, Bard, and LLaMA.
- Deep Dive into GPT:
- Architecture and attention mechanisms.
- Evolution: GPT-2, GPT-3, GPT-4.
- Hands-On Exploration:
- Interactive prompts to explore GPT’s language capabilities (e.g., summarization, brainstorming, content generation).
Session 3: Generative AI in the Software Development Lifecycle
- AI’s role across SDLC phases:
- Requirement gathering, coding, testing, deployment.
- Overview of upcoming tools and techniques.
Day 2: Generative AI for Coding and Collaboration
Session 1: AI-Assisted Coding
- Introduction to AI tools for coding:
- GitHub Copilot, Tabnine, and CodeT5.
- Hands-On Coding Exercises:
- Automating code generation, debugging, and documentation.
Session 2: AI in Software Design and Planning
- AI tools for planning: Notion AI, Whimsical, and Beautiful.ai.
- Hands-On Exercise:
- Generating diagrams, flowcharts, and requirement documents.
Session 3: Best Practices and Ethical Considerations
- Ensuring ethical AI usage in software development.
- Avoiding AI-generated code pitfalls (security, copyright issues).