Agentic AI
How to design AI systems that plan, decide, and act across multi-step tasks instead of just answering prompts.
One-time course fee
Who should take this?
Professionals and developers who need multi-step, tool-using AI systems rather than simple chat interfaces.
Capability developed
Scope, design, evaluate, and govern agents that use tools, memory, state, and human oversight.
Professional application
Research, knowledge, operations, support, or specialised agent implementation.
What’s inside this track
- 1Agentic Systems Foundations
Build: Map 3 agent use cases in a chosen business domain.
Evidence: Can tell a true agent from a scripted bot — and justify when one is actually warranted.
- 2Agent Architecture & Reasoning Patterns
Build: Design an Agent Architecture Blueprint (v1) for a real workflow.
Evidence: Can design an agent's control loop before writing a single line of code.
- 3Tools, Memory & Grounding
Build: Build a research + analysis agent wired to a real API.
Evidence: Ships an agent that reasons over real data — not a static prompt wearing a costume.
- 4Multi-Agent Systems & Production Readiness
Build: Capstone: a 2–3 agent team (research → draft → review) with logging and human override.
Evidence: Can ship a multi-agent system with the guardrails a paying client would actually require.
What you get
What you will own
Not a promise — a concrete list of what you personally build and can show a buyer, pulled from this course’s real curriculum.
- A working project: Map 3 agent use cases in a chosen business domain.
- A working project: Design an Agent Architecture Blueprint (v1) for a real workflow.
- A working project: Build a research + analysis agent wired to a real API.
- A working project: Capstone: a 2–3 agent team (research → draft → review) with logging and human override.
- A completed capstone: Enterprise Research Assistant with Multi‑Agent Workflow, scored across multiple dimensions
- A portfolio entry documenting how you built it, not just that you finished
- Verified skill evidence — tied to real work, not a self-rating
What you’ll prove — and own — by the end
Completion isn’t the finish line. This is what turns the course into evidence you can actually use.
Personalised from day one
A short entry diagnostic flags which modules to move through quickly and which to slow down on — the full curriculum stays available either way.
Evidence, not checkmarks
Skills track through a real mastery ladder — module completed, exercise practiced, project shipped — not just “lesson viewed.”
Your Final real-world project, AI-defended
Enterprise Research Assistant with Multi‑Agent Workflow — submit real work, defend your decisions to an AI interviewer, get scored feedback across multiple dimensions.
A portfolio you can use today
Turn a finished project into a case study, resume bullets, and an interview story — drafted from your real work, yours to review before you use it anywhere.
Connect this course to practical work
See how Ropes links a skill to a business problem, portfolio proof, a bounded service, and responsible client delivery. No client or income outcome is guaranteed.
Earnings potential
A simple illustration of how freelancers commonly structure retainer pricing once they’re taking on client work.
Agent-building retainer
Illustrative example — your results will vary based on niche, effort, and client base.
Industry snapshot
Real, sourced research — current tools, market signal, and named case studies, each with a citation. Not marketing copy.