Agentic AI Foundations: Agents, Tools, and Memory
Build your first AI agents from scratch — learn how agents use tools, maintain memory, and complete multi-step tasks autonomously. Free beginner course.
Course Content
Agentic AI Foundations
2026 is the year AI agents went from demos to production. This course teaches you to build them — from the first “Hello, Agent” to a fully capable research assistant that works autonomously.
Why Agentic AI?
The shift from chatbots to agents is the most important transition in applied AI. Agents don’t just respond — they plan, use tools, observe results, and iterate until a task is complete. They can browse the web, write and run code, query databases, and call APIs — all without a human in the loop.
This course gives you the conceptual foundations and hands-on practice to build agents that actually work in production.
What You’ll Build
- Research agent: Browses the web, extracts key information, and writes structured reports
- Code assistant agent: Generates, runs, debugs, and explains code autonomously
- Multi-step task agent: Breaks down a complex goal into subtasks and executes them in order
Connection to SuperML Products
NL-2-SQL Agents — one of SuperML’s open source products — is built on the exact agentic patterns taught in this course. You’ll study its architecture directly as a real-world case study.
📋 Prerequisites
- Basic Python programming
- Familiarity with calling an API (any language)
- Optional: completion of Prompt Engineering Fundamentals
🎯 What You'll Learn
- Understand how AI agents plan, use tools, and iterate toward a goal
- Build agents using LangChain that can search, reason, and report
- Implement short-term and long-term memory for stateful agents
- Design multi-agent workflows with clear task boundaries
- Add safety guardrails to prevent unintended agent actions