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Training
Certificate
Course Information
Course Name
DSCI-273: Generative AI Cloudera
Exam code
CDP-6001
Duration
2 Days
Overview
Audience Profile
Prerequisities
At Course Completion
Course Outline
Overview
Generative AI (GenAI) and Large Language Models (LLMs) are extremely powerful new tools that are changing every industry. To fully take advantage of GenAI and LLMs, these new capabilities need to be combined with your existing enterprise data. This two-day course teaches how to use Cloudera AI to train, augment, fine tune, and host LLMs to create powerful enterprise AI solutions.
Overview
Overview
Generative AI (GenAI) and Large Language Models (LLMs) are extremely powerful new tools that are changing every industry. To fully take advantage of GenAI and LLMs, these new capabilities need to be combined with your existing enterprise data. This two-day course teaches how to use Cloudera AI to train, augment, fine tune, and host LLMs to create powerful enterprise AI solutions.
Audience Profile
Audience Profile
The course is designed for data scientists and machine learning engineers who need to understand how to utilize Cloudera AI to leverage the full power of their enterprise data, generative AI, and Large Language Models and deliver powerful business solutions.
Prerequisities
Prerequisities
None
At Course Completion
At Course Completion
Through lecture and hands-on exercises, you will learn how to:
- Select the right LLM model for a use case
- Configure a Prompt for an LLM
- Use Retrieval Augmented Generation (RAG)
- Fine Tune an LLM Model with Enterprise Data
- Use the AI Model Registry and host an LLM
- Create an AI Agent with Crew AI
Course Outline
Course Outline
Module 1: Introduction to LLMs
- History of LLMs
- How Transformers Work
- Different Types of LLMs
- Limitations of LLMs
Module 2: LLM Model Selection
- How LLMs are Evaluated
- Model Selection by Use Case
- Hugging Face Model Hub
- Hands-On Exercise: Open LLM Leaderboard
- Hands-On Exercise: Can you run it? LLM Version
Module 3: Model Registries and Inference Services
- Cloudera AI Model Registry
- AI Inference Service
- Hands-On Exercise: Text Summarization with Amazon Bedrock
Module 4: Prompt Engineering
- Components of a Prompt
- Shot Prompting
- Hands-On Exercise: Prompt Engineering with Mistral
Module 5: Retrieval Augmented Generation
- Retrieval Augmented Generation (RAG)
- RAG Use Cases
- Hands-On Exercise: LLM Chatbot Augmented with Enterprise Data
- Hands-On Exercise: Intelligent QA Chatbot with NiFi, Pinecode, and Llama2
Module 6: Fine Tuning
- Motivation for Fine Tuning
- Principles of Fine Tuning
Module 7: Parameter Efficient Tuning
- Limitations of Fine Tuning
- Principles of Parameter Efficient Tuning
Module 8: Fine Tuning a Foundation Model
- Quantization
- Low Rank Adaptation
- Hands-On Exercise: Fine Tuning a Foundation Model for Multiple Tasks (with QLoRA)
Module 9: AI Agents
- Introduction to AI Agents
- AI Agent Architecture
- Hands-On Exercise: All Your Agents with Crew AI
