06 IBM Fundamentals of Building AI Agents
Fundamentals of Building AI Agents
Private Course
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| Responsible | Administrator |
|---|---|
| Last Update | 06/28/2026 |
| Completion Time | 3 hours 57 minutes |
| Members | 1 |
Advanced (RAG and Agentic AI)
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Module 0116Lessons · 3 hr 13 min
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01 Course Introduction.mp4
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02 course overview.pdf
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03 helpful tips.png
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04 RAG and Agentic AI Professional Certificate Overview.mp4
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05 What are AI Agents.mp4
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06 Comparing AI System Designs.pdf
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07 When to (and not to) use AI Agents.pdf
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08 Tool Calling for LLMs.mp4
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09 Why AI Needs Tools From Guessing to Real-World Action.mp4
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10 Tools, Agents, and Function Calling in LangChain.pdf
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11 Build Effective AI Tools for Advanced LLMs.mp4
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12 Build Intelligent Agents for Dynamic LLM Tool Use.mp4
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13 Build a Custom Math Toolkit Agent with LangChain.mp4
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14 Popular tools in lanchain.pdf
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15 cheatsheet v2.pdf
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15 summary
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Module 028Lessons · 20 min
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01 LangChain LCEL Chaining Method.mp4
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02 LangChain Expression Language (LCEL) cheatsheet.pdf
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03 When to Call Tools Manually.mp4
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04 Structured Outputs for Tool Calling.pdf
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05 Build LLM Agents with Tools.mp4
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06 Build Interactive LLM Agents.mp4
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07 cheatsheet.pdf
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07 summary
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Module 037Lessons · 24 min
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01 From Natural Language to Data Visualizations with LangChain.mp4
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02 How AI Transforms Analytics.pdf
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03 An Introduction to AI-Powered SQL Agents.mp4
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04 Implementing LangChain’s AI-Powered SQL Agent.mp4
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05 Natural Language Interfaces for Data Systems.pdf
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06 cheatsheet Using Built-in Agents in LangChain.pdf
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07 Course Wrap-Up.mp4
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