What You'll Learn

By the end of this course, you'll be able to:

Understand generative AI fundamentals

Build text generation models

Create image generation systems

Implement code generation tools

Fine-tune generative models

Evaluate generative outputs

Course Modules

A comprehensive curriculum designed for practical application.

1

Generative AI Fundamentals

  • What is generative AI?
  • Types of generative models
  • Applications overview
  • Ethical considerations
2

Large Language Models

  • Transformer recap
  • GPT architecture
  • LLM capabilities
  • Prompting basics
3

Prompt Engineering

  • Effective prompts
  • Chain-of-thought
  • Few-shot learning
  • Prompt templates
4

Fine-tuning LLMs

  • LoRA and QLoRA
  • Instruction tuning
  • RLHF basics
  • Domain adaptation
5

Text Generation

  • Text completion APIs
  • Creative writing
  • Code generation
  • Conversation systems
6

Image Generation

  • Diffusion models
  • Stable Diffusion
  • Image-to-image
  • Inpainting and outpainting
7

Multimodal AI

  • Vision-language models
  • Image captioning
  • Visual QA
  • Multimodal agents
8

RAG Systems

  • Retrieval-augmented generation
  • Vector databases
  • Embedding models
  • Hybrid search
9

AI Agents

  • Agent architectures
  • Tool use
  • Memory systems
  • Multi-agent collaboration
10

Building GenAI Applications

  • Application architecture
  • API integration
  • Safety and alignment
  • Production considerations

Enroll in Generative AI

Fill out the form below and we'll get back to you within 24 hours.