Building AI Agents for Complex Tasks
Key Takeaways
Designs and builds AI agents for complex tasks using architectures that perceive context and make decisions
Original Description
Building AI Agents for Complex Tasks is an intermediate-level course designed to equip learners with the skills to design, build, and evaluate intelligent agents that operate autonomously across dynamic, multi-step environments. Moving beyond simple chatbot flows, this course introduces learners to agent architectures that perceive context, make decisions, integrate tools, and recover from failure.
Through hands-on labs, interactive video walkthroughs, and real-world case studies—including Alexa, BabyAGI, and AlphaCode—learners will explore agent types, design patterns, tool orchestration, memory management, and behavior evaluation. They'll gain practical experience using modern frameworks like LangChain and Rasa to construct agents for use cases such as research automation, virtual assistants, and decision-making bots.
By the end of the course, learners will have built and tested their own intelligent agent and developed the foundational skills to implement agent-based AI systems that can adapt, reason, and act in real-world applications.
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Related Reads
📰
📰
📰
📰
My AI agents kept re-verifying the same work. So I made verification a signed, reusable object
Dev.to AI
I Built a Privacy-First Health Record MCP Server That Runs Entirely on Your Machine
Dev.to AI
Tessl Academy is live (in preview) — and there are two ways in
Dev.to AI
The Relationship Is the Product
Medium · AI
🎓
Tutor Explanation
DeepCamp AI