8 Practical AI Agent Building Courses

1. Fundamentals of AI Agents Using RAG and LangChain by IBM

• Learn retrieval-augmented generation (RAG) applications and processes.
• Focuses on prompt engineering for precise LLM responses.
• Introduces LangChain tools and components to simplify development.
• Provides hands-on lab practice developing applications with LLMs, LangChain, and RAG.
• Includes a real-world project suitable for job interviews.

2. Large Language Model Agents

• Covers fundamental LLM agent concepts and required abilities.
• Discusses infrastructures for agent development.
• Presents representative agent applications in various fields (e.g., code, robotics, medical).
• Addresses limitations and potential risks of current LLM agents.
• Shares insights into directions for future improvements.

3. AI Agentic Design Patterns with AutoGen

• Learn to make and customize multi-agent systems using AutoGen.
• Enables agents to take on different roles and collaborate.
• Covers design patterns like multi-agent collaboration and tool use.
• Includes projects like conversational chess and coding agents for financial analysis.
• Offers experience with integrating human feedback into agent workflows.

4. AI Agents in LangGraph

• Build an agent from scratch, then rebuild it using LangGraph.
• Learn about agentic search for providing better data to agents.
• Implement persistence for state management across conversations.
• Incorporate human-in-the-loop mechanisms into agent systems.
• Develop a practical agent for an essay writing task.

5. Serverless Agentic Workflows with Amazon Bedrock

• Build and deploy serverless agentic applications.
• Create agents with tools, code execution, and guardrails for safety.
• Use Amazon Bedrock for agent configuration and deployment.
• Connect agents to services like CRMs and knowledge databases.
• Implement guardrails to prevent the exposure of sensitive information and the use of inappropriate language.

6. Multi-AI Agent Systems with CrewAI

• Learn principles of designing effective AI agents and organizing agent teams.
• Automate common business processes using multi-agent systems.
• Work with CrewAI, an open-source library for multi-agent systems.
• Explore agent components like role-playing, memory, tools, and guardrails.
• Build agent crews for tasks like customer support and event planning.

7. Smol Agents: Build & Deploy by Hugging Face

• Study AI agents in theory, design, and practical application.
• Learn to use libraries like smolagents, LlamaIndex, and LangGraph.
• Share agents on the Hugging Face Hub and explore community creations.
• Participate in challenges to evaluate agents against others.
• Complete use-case assignments to solve real-world problems.

8. Advanced Large Language Model Agents

• Learn advanced topics like complex reasoning and planning for LLM agents.
• It focuses on AI applications in mathematics and programming.
• Study how LLMs can be used for mathematical theorem proving.
• Covers LLM techniques for generating and reasoning about computer programs.
• Introduces advanced inference and post-training techniques for agent building.

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