Confidence with basic diagrams and section terminology
Outcomes
Explain governance is enforcement in your own words and apply it to a realistic scenario.
Governance works when it is enforced by the system and measured by evidence.
Check the assumption "Owners exist" and explain what changes if it is false.
Check the assumption "Evidence is reviewable" and explain what changes if it is false.
Practice
Work through one scenario and justify the decision with evidence
Compare two options and name the trade-off clearly
Artefact and failure modes
A one-page decision note with assumption, evidence, and chosen action
Policy only in text. A policy that is not enforced is a wish.
No change control. If changes are not tracked, you cannot explain failures or defend outcomes.
Optional
Planning and evidence
Objectives, timing, and CPD tracking
Show
If you want to start learning now, leave this closed. Come back when you want to plan your practice or keep evidence for CPD. This is guidance and it is not endorsed by awarding bodies. Standards mapping lives on the course overview page.
Learning objectives
What you will be able to do
1. Explain the training loop in plain language and diagnose common failure modes like overfitting and leakage.
2. Design a basic evaluation plan (metrics + thresholds) that matches a real-world decision and risk profile.
3. Describe how data quality, features, and representation affect model behaviour in production.
4. Select an appropriate deployment pattern (batch, real-time, retrieval-augmented) and explain the trade-offs.
What changes at this level
Level expectations
Each level is independent but clearly deeper than the last. This panel makes the jump explicit.
Assessment intent
Applied
Scenario based evaluation and pipeline decisions, including drift and governance basics.
Style
scenario
12 questions
Pass standard
Coming next
Not externally certified
▸Evidence you can save (CPD friendly)
An evaluation plan for one real decision: metrics, thresholds, and what errors cost you.
A small prompt or RAG workflow note: inputs, guardrails, tests, and a red-team example.
A monitoring checklist: drift signals, quality sampling, and a clear rollback or disable plan.
CPD timing
Applied time breakdown
Defensible timing based on page content: reading, labs, checkpoints, and reflection.
Reading
50m
7,422 words × 1.3
Practice
150m
10 × 15m
Checkpoints
25m
5 × 5m
Reflection
40m
5 × 8m
Estimated total
4h 25m
Based on page content
Claimed hours
4h
Includes reattempts + capstone
CPD tracking
Fixed hours for this level are 4. Timed assessment time is included once on pass.
1. Explain the training loop in plain language and diagnose common failure modes like overfitting and leakage.
2. Design a basic evaluation plan (metrics + thresholds) that matches a real-world decision and risk profile.
3. Describe how data quality, features, and representation affect model behaviour in production.
4. Select an appropriate deployment pattern (batch, real-time, retrieval-augmented) and explain the trade-offs.
What changes at this level
Level expectations
Each level is independent but clearly deeper than the last. This panel makes the jump explicit.
Assessment intent
Applied
Scenario based evaluation and pipeline decisions, including drift and governance basics.
Style
scenario
12 questions
Pass standard
Coming next
Not externally certified
▸Evidence you can save (CPD friendly)
An evaluation plan for one real decision: metrics, thresholds, and what errors cost you.
A small prompt or RAG workflow note: inputs, guardrails, tests, and a red-team example.
A monitoring checklist: drift signals, quality sampling, and a clear rollback or disable plan.
Learning contract
Applied outcomes
About 4 hours
Read the explanation first, then use the tools to test the idea. Skip any tool that is not useful for your goal.
Explain the training loop in plain language and diagnose common failure modes like overfitting and leakage.
Design a basic evaluation plan (metrics + thresholds) that matches a real-world decision and risk profile.
Describe how data quality, features, and representation affect model behaviour in production.
Select an appropriate deployment pattern (batch, real-time, retrieval-augmented) and explain the trade-offs.
Eight modules turn vocabulary into production patterns
Each module of the Applied stage produces one production pattern. Stacked together, the eight modules form the seven patterns plus a capstone that the Practice stage assumes can be combined into systems.
The Applied stage turns the conceptual vocabulary from Foundations into seven production patterns plus a capstone that proves the patterns work together.
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Next step
Practise this level, then move on
I recommend you use the practice assessment for Applied to test your understanding and write a short reflection. Timed assessments are being prepared for this track.
Practice
Assessment
No timer
Pace
Reflection
Evidence
Practice assessment
Start the practice assessment for Applied
It is designed for confidence and evidence, and you can retry as often as you need.
The timed assessment for this level is being prepared. Use the practice assessment and labs until it is ready.
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During timed assessments, copy and the context menu are restricted to reduce casual cheating. Passed assessments are recorded in your account as evidence.
