Fundamentals of Building AI Agents Issued by IBM via Coursera Instructors: Joseph Santarcangelo, Kunal Makwana, Karan Goswami, Faranak Heidari
Intermediate-level course on building production AI agents with LangChain. Covered the distinction between traditional LLM workflows and reasoning agents, tool calling and chaining patterns, designing custom tools, LangChain Expression Language (LCEL) for structured workflows, manual tool calling for control over accuracy and cost, structured output parsing and validation, and pre-built DataFrame and SQL agents for natural-language data analysis. Labs included a math toolkit agent, an LCEL-powered data analysis pipeline, an interactive tool-calling agent, a data visualization agent, and a natural-language SQL agent.
Part of the IBM RAG and Agentic AI Professional Certificate and the Building AI Agents and Agentic Workflows Specialization.
Skills: LangChain, LCEL, AI Agents, Tool Calling, Function Calling, Structured Outputs, SQL Agents, DataFrame Agents, Agentic Workflows, Prompt Engineering