Introduction
Building generative AI with no code
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1. Generative AI (GenAI) Foundations
Business applications with GenAI
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Understanding capabilities of GenAI
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2. Building Products with GenAI
Build GenAI products using the 1-2-3 framework
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Understanding pre-training, fine-tuning, and inference models
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Demo: Chat with your data with GPT using Akkio
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Challenge: Chat with a dataset using GPT with no code
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Solution: Chat with a dataset using GPT with no code
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3. AI Assistant for Enterprise Summarization
What are foundational GenAI models?
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Fine-tuning and retrieval augmented generation (RAG)
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Demo: Build an AI assistant for text summarization or query a book with h2oGPT
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Demo: Summarize a video meeting using Gemini
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Challenge: Summarize a customer meeting video with an AI assistant
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Solution: Summarize a customer meeting video with an AI assistant
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4. AI Agents with AgentGPT
What is an AI agent?
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Demo: Build an AI agent using AgentGPT
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Challenge: Build an AI agent to research your industry
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Solution: Build an AI agent to research your industry
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5. Business Considerations
Understanding the token costs of generative AI
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Selecting GenAI models: Open-source vs. closed platforms
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Hallucinations and ethical considerations for GenAI
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Choosing between fine-tuning vs. RAG
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Conclusion
Closing out and next steps
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Ex_Files_No_Code_GenAI.zip
(52 KB)