Development>AI & Data Science>AI Agents & Agentic AI Engineering
AI Agents & Agentic AI Engineering
Design, build, and orchestrate autonomous multi-step agents with tool use, memory systems, and human-in-the-loop controls.
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(1,240 ratings)8,420 studentsCreated by AI School Instructor Team
Last updated 8/2026
English [Auto]
What you'll learn
Architect single and multi-agent systems with ReAct, Plan-and-Execute, and Reflexion patterns
Design reliable tool schemas and execution environments with automated error recovery
Implement multi-tier short-term and persistent long-term agent memory
Orchestrate multi-agent workflows using state machines and communication protocols
Implement human-in-the-loop approval gates and runaway execution controls
Course Curriculum & Modules
8 Modules Total🔒 Module overview and core resources are locked. Pay and enroll in the cohort to unlock full materials.
Lessons:
What Makes Something an "Agent"?
🔒 Core notes, hands-on notebooks, and video session are locked.
The Core Agent Loop
🔒 Core notes, hands-on notebooks, and video session are locked.
Overview of Agent Architectures
🔒 Core notes, hands-on notebooks, and video session are locked.
Where Agents Fit vs Simple Automation
🔒 Core notes, hands-on notebooks, and video session are locked.
Quiz 1: Agent Foundations (12 Questions) 🔒
End-of-Course Capstone
Autonomous Multi-Tool Agent with Human Checkpoint
🔒 The capstone project involves designing, building, and deploying a production-grade enterprise application. Cohort students receive 1-on-1 code reviews and sandbox hosting credits. Pay and enroll to unlock Capstone instructions.
Capstone Deliverables:
4 Capstone Deliverables (Locked — Pay to unlock)
Grading Rubric (100 Points Total)
30 pts
Agent Planning, Reflection & Loop Stability
25 pts
Tool Schema Robustness & Error Handling
25 pts
Memory Architecture & State Recovery
20 pts
Human-in-the-loop Checkpoint & Safety Bounding
Summative Evaluation
Agentic AI Engineering Final Certification Exam
Exam Duration
90 Minutes
| Section | Name | Questions | Points | Type |
|---|---|---|---|---|
| A | Agent Foundations & Core Patterns | 15 Qs | 30 pts | MCQ / Multi-select |
| B | Applied Multi-Step Scenarios | 10 Qs | 30 pts | Scenario-based MCQ + Short Answer |
| C | Trajectory & Trace Analysis | 8 Qs | 25 pts | Trajectory debugging & loop analysis |
| D | Multi-Agent System Design | 1 Qs | 15 pts | Rubric-graded system architecture |
Sample Section D System Design Prompt:
"Design a multi-agent system to triage and draft responses to incoming customer emails, with a human approval step before sending. Specify agent roles, tools each needs, memory requirements, and where the human-in-the-loop checkpoint sits."
Preview this course
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Full Lifetime Access • Learn on Your Pace
This course includes:
- 8 modules breakdown
- 2 modules/week (~4–5 hrs/week) learning pace
- Full text read-along with synced audio reader
- Module → Lesson → Quiz → Assignment curriculum layout
- Official PDF Certificate of completion
Interactive Quiz Preview
Test your knowledge with sample formative questions from the curriculum question bank.
Quiz Sandbox Locked
Interactive quiz testing is available only for enrolled students of this cohort.