Build & Test AI Agents, ChatBot, RAG with Ollama & Local LLM

Übersicht

Build & Test AI Agents, Chatbots, and RAG with Ollama & Local LLMs

Lehrplan

• Introduction to AI Agents
Overview of AI Agents
Characteristics of Intelligent Agents
Types of AI Agents and their applications
• Chatbot Development
Fundamentals of Chatbots
Designing Chatbot Conversations
Key Technologies for Building Chatbots
• Understanding Retrieval-Augmented Generation (RAG)
Introduction to RAG
How RAG Models Work
Advantages of RAG in NLP Applications
• Ollama Platform Overview
Setting Up the Ollama Development Environment
Key Features of Ollama
Integrating Ollama with AI Projects
• Local Large Language Models (LLM)
Understanding LLM Frameworks
Installing and Running Local LLMs
Use Cases for Local LLMs
• Building AI Agents with Ollama and Local LLMs
Constructing an AI Agent Architecture
Implementing AI Agents using Ollama
Testing AI Agents Locally
• Developing and Deploying a Chatbot
Step-by-Step Chatbot Deployment
Integrating Chatbots with Ollama
Debugging and Optimizing Performance
• Implementing Retrieval-Augmented Generation (RAG)
Setting Up RAG Models Locally
Customizing Retrieval for Information Accuracy
Application of RAG in Real-world Scenarios
• Testing and Evaluation
Metrics for Evaluating AI Agents
Stress Testing Chatbots and RAG Models
Iterative Improvement Processes
• Real-world Use Cases and Projects
Case Studies of AI Agents and Chatbots
Hands-on Projects with Guided Instructions
Collaborative AI Development Workshops
• Future Trends in AI and LLM
Emerging Technologies in AI
Ethical Implications of AI Agents
Preparing for Advanced AI Developments
• Conclusion and Next Steps
Recap of Course Learnings
Resources for Further Study
Establishing a Continued Learning Path in AI

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Unterrichtet von

Karthik KK

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Fachgebiete

Computer Science