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AI-202 AI & Data

Feature Engineering & Model Evaluation Mastery

The craft course that separates competent from excellent: engineering predictive features from raw business data and choosing evaluation schemes that survive production. Includes temporal cross-validation, class imbalance, calibration and cost-sensitive metrics.

B3Practitioner
5modules
35skill atoms
2role journeys
Curriculum

What this course covers.

5 modules, 35 named skill atoms. Expand any module to see them.

1Feature Craft7 skill atoms
interactionsaggregatestarget encoding safelyratio & difference featuresdatetime decompositionfrequency encodingfeature count vs sample size
2Temporal Correctness7 skill atoms
point-in-time joinstemporal CVdrift previewexpanding-window splitsembargo gapslabel horizon definitionbacktest calendars
3Imbalance & Calibration7 skill atoms
resamplingthresholdscalibration curvesSMOTE trade-offsclass weights vs resamplingPlatt & isotonic scalingBrier score
4Business-Aligned Metrics7 skill atoms
cost matricesprecision@kdecision analysisexpected value per decisionlift & gain curvesPR-AUC vs ROC-AUC choicecapacity-constrained queues
5Evaluation Clinic7 skill atoms
critique flawed evalsredesigndefendleakage post-mortemstest-set reuse detectionmissing baselinesreproducible eval script
Where it fits

AI-202 in the role journeys.

This course appears in 2 of our 45 role journeys. Here is what a learner takes immediately before and after it in each.

AI / ML Engineer

Practitioner stage
AI-201AI-202AI-203

Data Scientist

Practitioner stage
AI-201AI-202AI-108

Roles this course serves

The capability ladder

This course is authored to band B3.

Every course we run is written to one rung of the CASI ladder, so a plan can be assembled to take a team from where they are to where they need to be.

What do B1–B6 mean?The CASI Capability Ladder — click to expand

Every course targets a band on the CASI Capability Ladder — our six-band proficiency scale, anchored to open standards (O*NET, ESCO, NICE, NIST AI RMF, Bloom's). A band tells you how deep a course goes, and what evidence proves it.

What the learner can doTypical evidence
B1
AwareUnderstands concepts and vocabulary; uses tools with guidance
Knowledge checks
B2
FoundationPerforms standard tasks correctly in familiar contexts
Guided labs, autograded exercises
B3
PractitionerDelivers complete pieces of work independently
Scenario labs, proctored hands-on exams
B4
ProfessionalHandles production-grade complexity, trade-offs and failure modes
Break-fix drills, design defenses
B5
AdvancedEngineers systems end-to-end under constraints; leads others
Rubric-scored capstones, vivas
B6
ExpertSets direction; recognised authority across teams
Portfolio + panel evaluation

A note on B6. Courses in this catalog target B1–B5. B6 is not taught — it is recognised, through a portfolio and a panel, once someone is setting direction for others. Every journey here is built to land a learner at B5.

Next step

Run AI-202 for your team.

This course runs at several lengths depending on how deep you need to go and how much of it your people already have. Tell us who is being trained and we will scope it.

Add it to a training plan Talk to our team Check your team’s level free