Course Overview

About Course

The Architecting AI Agents program is a comprehensive 40‑hour course tailored for software engineers, AI developers, and solution architects. It’s centered on building robust, autonomous, production-grade agentic systems using state-of-the-art frameworks and practices.

Drawing from leading platforms like Coursera’s “AI Agents and Agentic AI Architecture in Python” and Databricks’ enterprise-grade agent design, the training emphasizes foundational theory, hands-on implementation, and production readiness

Participants start by understanding what defines an AI agent—an autonomous system that observes its environment, reasons using reasoning frameworks like ReAct or Chain‑of‑Thought, and acts via APIs or tools. Core architecture principles include selecting the right LLM as a central reasoning engine, integrating memory modules, ensuring tool access, and designing safety mechanisms following the MATE (Modular, Autonomous, Trustworthy, Evaluatable) framework .

The course features heavy hands-on labs where participants implement agents in Python, integrating retrieval-augmented generation (RAG) using vector stores like Databricks Mosaic AI, and creating multi-agent orchestration workflows .Labs include self‑prompting patterns, expert personas, tool handling, logging, reversible actions, and safety constraints.

Next, learners explore multi-agent coordination, architecting systems where specialized agent roles communicate, share memory, and execute collaboratively—mirroring real-world use cases like resume tailoring, research assistance, or customer support

Finally, the program covers production readiness: deploying agents in scalable, secure environments like serverless or containerized setups; monitoring and evaluating via metrics such as success rates, latency, and token cost; and ensuring observability, traceability, and ethical alignment within enterprise systems .

By the end of the training, participants will be able to design, implement, evaluate, and deploy autonomous AI agents—equipped with strong safety, observability, and real-world deployment strategies. This makes the course ideal for those aiming to build intelligent, autonomous systems capable of executing complex workflows safely and at scale.