Generative AI for Developers

Course Duration

3 Days

Audience

Employees of federal, state and local governments; and businesses working with the government.

Prerequisites

No prerequisites required.

Course Description

This course introduces developers to the principles and practical applications of Generative AI. Students learn how large language models work, how to integrate GenAI APIs into applications, prompt engineering techniques, retrieval-augmented generation, and responsible AI practices — enabling them to build intelligent, AI-powered features into real-world software.

Learning Objectives

• Build a solid understanding of generative AI techniques and their applications in software.
• Gain hands-on experience with popular models,including GANs, VAEs, and Transformers.
• Learn to utilize AI as your paired programming partner
• Gain hands on experience creating AI assisted requirements, design, code and tests
• Address ethical, legal, and safety considerations of generative AI, including bias mitigation and responsible content generation.

Course Outline

• Introduction to Generative AI Understand generative AI concepts and applications.
• Trace the evolution of generative AI technologies.
• Identify types of generative models and their uses.
• Learn key concepts: machine learning, neural networks, transformers.
• Review popular generative models like GPT and Codex.
• Introduction to Prompt Engineering Explore prompts' role in guiding AI outputs.
• Craft effective prompts for various tasks.
• See how prompt specificity shapes results.
• Experiment with prompt variations for desired outcomes.
• Deep Dive into AI Models Understand architectures of popular AI models.
• Ask, Edit, or Agent mode
• ChatGPT, Claude sonnet, Grok
• Evaluate free and premium models for AI assisted development
• Utilize AI assisted coding in your IDE
• Assess model performance and limitations.
• The SDLC and Environment Setting up your development environment
• Understanding the SDLC
• Choosing tools and AI models
• Establishing rules for iterative development
• Developing Application Requirements Step 1 – creating a product objectives document
• Step 2 – Create User Stories (use-cases) for critical features
• Step 3 – Review
• Architecture AI assisted design
• Using mermaid to depict architecture
• Generating design documents
• AI Assisted Design AI assisted test-driven design
• Creating an object-model
• AI generated documentation and mermaid diagrams
• AI Assisted Coding Inline code assistance
• Agent mode coding