Hands on – Building Intelligent Agents with LLMs

Master LLM Agents for Advanced Reasoning, Coding Assistants, Research Assistants, and More through Hands-On Code

Created by: Priyanka Dwivedi
Seasoned AI Consultant

What Will I Learn?

• Understand the key differences between LLM prompt output, LLM Chains, Retrieval-Augmented Generation (RAG), and LLM Agents.
• List and explain the main components of an LLM Agent, including tools, memory, and planning mechanisms
• Utilize sophisticated task planning and reflection methods to enhance the functionality and efficiency of LLM Agents
• Create and implement memory mechanisms that enable LLM Agents to sustain interaction and learn over time.
• Incorporate different tools to extend and enhance the capabilities of LLM Agents.
• Combine components to create complex agents such as Research Assistants, Coding Assistants, Recommendation Agents, and Agentic RAGs.
• Engage in 15 interactive coding tutorials that progressively build on concepts, providing practical experience and deeper understanding.

Requirements

• Basic Python Programming experience
• Basic understanding of Generative AI like LLMs, writing prompts etc

Target audience

• Aspiring AI specialists seeking to understand and leverage the power of LLMs
• Software developers looking to innovate with Generative AI-driven applications
• Data scientists aiming to broaden their expertise into AI agent design
• Technologists curious about the integration of Generative AI in practical tools and services