DeepLearning.AI
Learn how to build an agent that can reason over your documents and answer complex questions. This course will teach you to design and debug agents capable of intelligent navigation, summarization, and comparison of information across multiple documents.
Join our new short course and learn from Jerry Liu, co-founder and CEO at LlamaIndex, to start using agentic RAG, a framework designed to build research agents skilled in tool use, reasoning, and decision-making with your data. You will build various types of agents, including a router agent for Q&A and summarization tasks, and a research assistant agent capable of handling multiple documents. This course will enhance your ability to engage with and analyze your data comprehensively.
Python Enthusiasts
Anyone who has basic Python knowledge and wants to learn how to quickly build agents that can reason over their own documents.
AI Developers
Developers interested in building intelligent agents capable of reasoning, decision-making, and tool use with data.
Data Scientists
Data scientists looking to enhance their ability to engage with and analyze data comprehensively using agentic AI.
This course will teach you to build intelligent agents capable of reasoning over documents and answering complex questions. Ideal for Python enthusiasts, AI developers, and data scientists, it will enhance your ability to engage with and analyze data comprehensively.
1 / 3
Basic Python knowledge
Interest in AI and machine learning
Familiarity with data analysis concepts
Jerry Liu
Co-founder/CEO, LlamaIndex
Jerry Liu is the co-founder and CEO of LlamaIndex. He is passionate about making AI more accessible and democratized.
Cost
Free
Duration
Dates
Location