AI Agents course

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Core path

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Pick up where you left off

Train, then verify Isolation and routing Ship, observe, recover Experiment, then decide

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Full module map

Use this if you want the shape of the level before you start

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Module 5.1Train, then verify

Fine tuning is worthwhile only when you can test the win and the risk.

Open

Prerequisites

Comfort with earlier modules in this track
Ability to explain trade-offs and risks without jargon

Outcomes

Explain train, then verify in your own words and apply it to a realistic scenario.
Fine tuning is worthwhile only when you can test the win and the risk.
Check the assumption "Training data is safe" and explain what changes if it is false.
Check the assumption "Evaluation includes regressions" and explain what changes if it is false.

Practice

Solve a complex scenario with explicit assumptions and constraints
Write one mitigation plan and one fallback plan

Artefact and failure modes

A concise design or governance brief that can be reviewed by a team
Memorisation. A tuned model can regurgitate training data. Test for it.
Behaviour drift. A change that improves one task can silently worsen another.

Module 5.2Isolation and routing

Enterprise agents succeed when tenants are isolated and requests are routed by risk and cost.

Open

Prerequisites

Comfort with earlier modules in this track
Ability to explain trade-offs and risks without jargon

Outcomes

Explain isolation and routing in your own words and apply it to a realistic scenario.
Enterprise agents succeed when tenants are isolated and requests are routed by risk and cost.
Check the assumption "Tenant data is isolated" and explain what changes if it is false.
Check the assumption "Routing rules are explicit" and explain what changes if it is false.

Practice

Solve a complex scenario with explicit assumptions and constraints
Write one mitigation plan and one fallback plan

Artefact and failure modes

A concise design or governance brief that can be reviewed by a team
Cross tenant leakage. One leaked prompt or log line is enough to break trust and create legal risk.
Cost spikes. If routing always chooses the biggest model, your bill becomes a surprise.

Module 5.3Ship, observe, recover

Production systems need packaging, monitoring, and a plan for failure.

Open

Prerequisites

Comfort with earlier modules in this track
Ability to explain trade-offs and risks without jargon

Outcomes

Explain ship, observe, recover in your own words and apply it to a realistic scenario.
Production systems need packaging, monitoring, and a plan for failure.
Check the assumption "Health checks are real" and explain what changes if it is false.
Check the assumption "Rollback is possible" and explain what changes if it is false.

Practice

Solve a complex scenario with explicit assumptions and constraints
Write one mitigation plan and one fallback plan

Artefact and failure modes

A concise design or governance brief that can be reviewed by a team
Silent degradation. The agent can be wrong slowly. Monitor quality signals, not only uptime.
Runaway cost. A broken loop can burn tokens and tool calls until you hit a budget limit.

Module 5.4Experiment, then decide

Treat research as a pipeline. Try ideas safely, evaluate honestly, then adopt deliberately.

Open

Prerequisites

Comfort with earlier modules in this track
Ability to explain trade-offs and risks without jargon

Outcomes

Explain experiment, then decide in your own words and apply it to a realistic scenario.
Treat research as a pipeline. Try ideas safely, evaluate honestly, then adopt deliberately.
Check the assumption "Experiments are safe" and explain what changes if it is false.
Check the assumption "Evaluation is comparable" and explain what changes if it is false.

Practice

Solve a complex scenario with explicit assumptions and constraints
Write one mitigation plan and one fallback plan

Artefact and failure modes

A concise design or governance brief that can be reviewed by a team
Hype adoption. If you adopt because it is popular, you inherit failure modes you did not choose.
No exit strategy. If a new technique fails, you need a path back to the last safe version.

What changes at this level

Level expectations

Each level is independent but clearly deeper than the last. This panel makes the jump explicit.

Learning contract

Practice assessment outcomes

Read the explanation first, then use the tools to test the idea. Skip any tool that is not useful for your goal.

This is a scored practice assessment. It is free and not timed. Use it to sharpen judgement before the timed stage assessment.

Practice assessment bank not found for this level yet.

What to do next

Write a short review note on one miss and the assumption behind it.
Add one concrete guardrail that would have prevented that miss.
Retake the practice set, then move to the timed stage assessment.

Start timed assessment CPD prep pack Back to stage

Course materials are protected by intellectual property rights.View terms

Loading lesson...

Core path

Your path through this level

Progress saves in this browser and syncs after you sign in

Completed

0 of 4

Pick up where you left off

Train, then verify Isolation and routing Ship, observe, recover Experiment, then decide

Optional

Full module map

Use this if you want the shape of the level before you start

Show

Module 5.1Train, then verify

Fine tuning is worthwhile only when you can test the win and the risk.

Open

Prerequisites

Comfort with earlier modules in this track
Ability to explain trade-offs and risks without jargon

Outcomes

Explain train, then verify in your own words and apply it to a realistic scenario.
Fine tuning is worthwhile only when you can test the win and the risk.
Check the assumption "Training data is safe" and explain what changes if it is false.
Check the assumption "Evaluation includes regressions" and explain what changes if it is false.

Practice

Solve a complex scenario with explicit assumptions and constraints
Write one mitigation plan and one fallback plan

Artefact and failure modes

A concise design or governance brief that can be reviewed by a team
Memorisation. A tuned model can regurgitate training data. Test for it.
Behaviour drift. A change that improves one task can silently worsen another.

Module 5.2Isolation and routing

Enterprise agents succeed when tenants are isolated and requests are routed by risk and cost.

Open

Prerequisites

Comfort with earlier modules in this track
Ability to explain trade-offs and risks without jargon

Outcomes

Explain isolation and routing in your own words and apply it to a realistic scenario.
Enterprise agents succeed when tenants are isolated and requests are routed by risk and cost.
Check the assumption "Tenant data is isolated" and explain what changes if it is false.
Check the assumption "Routing rules are explicit" and explain what changes if it is false.

Practice

Solve a complex scenario with explicit assumptions and constraints
Write one mitigation plan and one fallback plan

Artefact and failure modes

A concise design or governance brief that can be reviewed by a team
Cross tenant leakage. One leaked prompt or log line is enough to break trust and create legal risk.
Cost spikes. If routing always chooses the biggest model, your bill becomes a surprise.

Module 5.3Ship, observe, recover

Production systems need packaging, monitoring, and a plan for failure.

Open

Prerequisites

Comfort with earlier modules in this track
Ability to explain trade-offs and risks without jargon

Outcomes

Explain ship, observe, recover in your own words and apply it to a realistic scenario.
Production systems need packaging, monitoring, and a plan for failure.
Check the assumption "Health checks are real" and explain what changes if it is false.
Check the assumption "Rollback is possible" and explain what changes if it is false.

Practice

Solve a complex scenario with explicit assumptions and constraints
Write one mitigation plan and one fallback plan

Artefact and failure modes

A concise design or governance brief that can be reviewed by a team
Silent degradation. The agent can be wrong slowly. Monitor quality signals, not only uptime.
Runaway cost. A broken loop can burn tokens and tool calls until you hit a budget limit.

Module 5.4Experiment, then decide

Treat research as a pipeline. Try ideas safely, evaluate honestly, then adopt deliberately.

Open

Prerequisites

Comfort with earlier modules in this track
Ability to explain trade-offs and risks without jargon

Outcomes

Explain experiment, then decide in your own words and apply it to a realistic scenario.
Treat research as a pipeline. Try ideas safely, evaluate honestly, then adopt deliberately.
Check the assumption "Experiments are safe" and explain what changes if it is false.
Check the assumption "Evaluation is comparable" and explain what changes if it is false.

Practice

Solve a complex scenario with explicit assumptions and constraints
Write one mitigation plan and one fallback plan

Artefact and failure modes

A concise design or governance brief that can be reviewed by a team
Hype adoption. If you adopt because it is popular, you inherit failure modes you did not choose.
No exit strategy. If a new technique fails, you need a path back to the last safe version.

What changes at this level

Level expectations

Each level is independent but clearly deeper than the last. This panel makes the jump explicit.

Learning contract

Practice assessment outcomes

Read the explanation first, then use the tools to test the idea. Skip any tool that is not useful for your goal.

This is a scored practice assessment. It is free and not timed. Use it to sharpen judgement before the timed stage assessment.

Practice assessment bank not found for this level yet.

What to do next

Write a short review note on one miss and the assumption behind it.
Add one concrete guardrail that would have prevented that miss.
Retake the practice set, then move to the timed stage assessment.

Start timed assessment CPD prep pack Back to stage

Course materials are protected by intellectual property rights.View terms

AI agents practice assessment. Advanced mastery

Level expectations

Practice assessment outcomes

AI agents practice assessment. Advanced mastery

Level expectations

Practice assessment outcomes