AI-201
Advanced Multi-Agent Systems & Autonomous LLM Architectures
Design advanced agent systems using ReAct, memory, planning, reflection, supervisor-worker swarms, graph orchestration, human-in-the-loop control and sandboxed execution.
Overview
Design advanced agent systems using ReAct, memory, planning, reflection, supervisor-worker swarms, graph orchestration, human-in-the-loop control and sandboxed execution.
- Format
- Self-study, online, at your own pace
- Level
- Year 2 academic
- Study load
- 4 Northline semester credits · approximately 180 total student-effort hours
- Prerequisites
- AI-106 and asynchronous Python
- Delivery
- Online · protected Northline Student Portal
What you will learn
- Design multi-agent system architectures
- Implement planning, memory and reflection patterns
- Coordinate supervisor-worker agent workflows
- Apply human approval and safety controls
- Build and assess an advanced autonomous-system project
Modules & lessons
Topics covered
ReAct
Memory
Planning
Reflection
Supervisor-worker swarms
Graph orchestration
Human-in-the-loop control and sandboxed execution
How self-study works
This is a self-study course. You work through it online, on your own schedule. There are no scheduled classes or live sessions to join.
- Go in order. Each module builds on the one before it.
- Practise as you go. Complete the activities and checks in each module before moving on; they show you what to revisit.
- Keep your work. Save your notes, drafts and evidence in your own document so you can reuse them.
- Get help when you need it. Questions about access or your account go to Student Support.
Assessment & certificate
Structured lessons, guided exercises or labs where applicable, review questions, final assessment and applied project/capstone work according to the released course package.
Certificate. Learners who complete the required lessons and exercises, pass the required mastery checkpoints and complete the capstone where applicable can receive an ARQS Course Completion Certificate. ARQS certificates are private professional-development credentials, not government accreditation, professional licensure or externally recognized academic credentials. How ARQS certificates work
ARQSI · AI course tutor
Study with ARQSI
ARQSI is the ARQS AI course tutor. This space is reserved for ARQSI, which will help you work through the course one lesson at a time: explaining each idea, setting short practice exercises and checking your understanding before you move on.
Until ARQSI opens here, study the modules on your own and contact Student Support with any questions about access.
Important limits
Northline defines one semester credit as approximately 45 hours of total student academic effort. External transferability or accreditation equivalence is not implied. The purchase listing and its fulfillment terms are separate from program admission. Immediate learner access and a confirmed academic start are not established by a purchase link; confirm availability with admissions.
Ready to start?
Advanced Multi-Agent Systems & Autonomous LLM Architectures
Enrollment price: $99