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AI Agent Developer | Coursera
You’ll learn to design agent architectures, implement tool use and memory, build custom GPTs, and apply best practices for responsible, trustworthy AI. By the end, you’ll be able to create and deploy intelligent software agents for real-world tasks across a range of industries.
AI Agent Development Fundamentals - Coursera
Learn the key components that make agents work, perception, reasoning, action selection, and execution loops. You’ll compare reactive, deliberative, and hybrid designs, and see how prompt templates and state management enable multi-turn interactions.
Master AI Coding Agents for Advanced Software Development
This Specialization teaches you how to use three leading AI coding agents — Google Antigravity, Claude Code, and OpenClaw — to speed up development, automate tasks, and build real software projects.
Best Agentic AI Courses & Certificates [2026] | Coursera
Some of the best online courses for agentic AI include the IBM RAG and Agentic AI Professional Certificate and the Agentic AI and AI Agents for Leaders Specialization.
Building AI Agents and Agentic Workflows | Coursera
You’ll start with LangGraph, creating agents that support memory, iteration, conditional logic, and retrieval-augmented generation (Agentic RAG). Next, you’ll explore self-improving agents that use reflection and reasoning, and design multi-agent systems that collaborate through orchestration.
AI Agents: Design and Build Agent Workflows | Coursera
In this course, you’ll learn how to design agents that go beyond language generation to reason, take action, and tackle real-world tasks using tools and data. During the course, you'll explore the foundations of tool calling and chaining with LangChain.
Build Powerful AI Agents with OpenAI Tools - Coursera
Each course builds toward real-world agent applications, from creating custom tools and multi-agent workflows to deploying production-grade agents with modern UI frameworks.
AI Agents and Agentic AI with Python & Generative AI - Coursera
You’ll explore how Python decorators can keep tool definitions and documentation in sync, how to organize tools using tags and registries, and how to simplify agent development through reusable, well-structured tool systems.
Master Agentic AI: Core Principles & Real-World PC
Learn agent design, MLOps, and security governance with hands-on projects for ML/AI practitioners. Design modular agent architectures and translate goals into reward signals for aligned behavior. Build CI/CD and retraining pipelines that detect drift and promote vetted models to production.
AI Agents: From Foundations to Applications | Coursera
AI Agents : From Foundations to Applications. This three-course specialization takes AI practitioners, developers, and researchers through the full lifecycle of AI agent development — from understanding intelligent agent theory to implementing and deploying autonomous, learning-driven systems.
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