Understanding the token costs of generative AI

Building generative AI with no code

Business applications with GenAI

Understanding capabilities of GenAI

Build GenAI products using the 1-2-3 framework

Understanding pre-training, fine-tuning, and inference models

Demo: Chat with your data with GPT using Akkio

Challenge: Chat with a dataset using GPT with no code

Solution: Chat with a dataset using GPT with no code

What are foundational GenAI models?

Fine-tuning and retrieval augmented generation (RAG)

Demo: Build an AI assistant for text summarization or query a book with h2oGPT

Demo: Summarize a video meeting using Gemini

Challenge: Summarize a customer meeting video with an AI assistant

Solution: Summarize a customer meeting video with an AI assistant

What is an AI agent?

Demo: Build an AI agent using AgentGPT

Challenge: Build an AI agent to research your industry

Solution: Build an AI agent to research your industry

Selecting GenAI models: Open-source vs. closed platforms

Hallucinations and ethical considerations for GenAI

Choosing between fine-tuning vs. RAG

Closing out and next steps