What you'll Learn
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Explore the latest advancements in Generative AI, including function calling and agentic capabilities.
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Understand the role of vector databases as the backbone of AI architectures like RAG and agents.
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Learn how to integrate your data into AI workflows as a knowledge base for enhanced functionality.
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Discover practical insights on function calling and building AI agents for advanced applications.
Who Should Enroll?
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Professionals: Gain hands-on knowledge to build AI agents that leverage your organization's data through memory systems like vector databases—perfect for enhancing intelligent automation and decision-making.
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Aspiring Students: Explore how cutting-edge generative AI tools like RAG and AI agents work and how to integrate memory, context, and tool use into AI agents.
About the Instructor
Tuana Çelik, Developer Relations and AI Engineering at Weaviate
Tuana Çelik is a Developer Relations Engineer at Weaviate. In her role, she educates the open-source community about AI tools, the latest methods, and workflows. Previously, she led the Developer Relations team at Deepset, the company behind Haystack.
About Author
JP Hwang , Developer Educator @ Weaviate | Data science & tech education
JP Hwang is passionate about empowering others to build with AI. He brings a combination of technical expertise, empathy, and bad jokes to all his endeavors to make learning fun and empowering for both sides.
FAQ's
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What is a vector database, and why is it important in agentic AI?
A vector database stores data in a format that enables similarity search, which is crucial for AI agents to retrieve relevant information from large datasets efficiently. It powers capabilities like semantic search in RAG and memory in AI agents.
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How does this course explain “memory” in AI agents?
Memory in AI agents refers to the ability to store and recall past interactions or external knowledge. The course covers how vector databases and structured memory systems enable this behavior.
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Will I receive a certificate upon completing the course?
Yes, the course provides a certification upon completion.
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What tools or platforms will be covered?
You'll be introduced to vector databases (Weaviate) and Retrieval-Augmented Generation (RAG), and how they fit into the agentic AI ecosystem.
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Does the course differentiate between types of memory (short-term vs long-term) in AI?
Yes, it discusses the role of both short-term (session-based) and long-term memory (persistent vector storage) in building effective agentic systems.