Applied AI and Machine Learning Foundations
A baseline ML exercise and bounded applied-AI prototype. Train/test separation is justified, baselines are compared and generated outputs are evaluated; no research-model mastery claim.
Register your interest. Dates and delivery are confirmed before enrolment opens.
What you will be able to do.
Build understanding, put it into practice and finish with work you can explain.
- Train/test separation is justified, baselines are compared and generated outputs are evaluated; no research-model mastery claim.
Is this for you?
Intermediate learners who can demonstrate the entry competencies listed below. Preparation suggestions are optional.
Before you begin
Read a JSON file and test a Python function Calculate a total and identify a duplicate in a supplied sheet
How you will show your progress
Train/test separation is justified, baselines are compared and generated outputs are evaluated; no research-model mastery claim.
From first principles to applied work.
Explain → Demonstration → Guided practice → Review
Planned outline. Lessons, trainer and schedule are confirmed before this course opens.
01240 live minutesDefine prediction versus generation tasks
45 min explanation · 45 min demonstration · 105 min practice · 45 min review
Distinguish prediction generation and rule-based tasks
02360 live minutesPrepare datasets and prevent leakage
70 min explanation · 70 min demonstration · 160 min practice · 60 min review
Prepare data with train-test separation and leakage checks
03360 live minutesBuild and evaluate simple supervised models
70 min explanation · 70 min demonstration · 160 min practice · 60 min review
Train and evaluate one simple supervised baseline
04360 live minutesCompare baselines and feature choices
70 min explanation · 70 min demonstration · 160 min practice · 60 min review
Compare features and models under the same split
05480 live minutesUnderstand generalisation uncertainty and bias
95 min explanation · 95 min demonstration · 215 min practice · 75 min review
Explain generalisation uncertainty and limitations
06360 live minutesUse model APIs and structured outputs
70 min explanation · 70 min demonstration · 160 min practice · 60 min review
Call a model API using typed validated outputs
07360 live minutesIntroduce retrieval and grounded generation
70 min explanation · 70 min demonstration · 160 min practice · 60 min review
Build a small retrieval-grounded example
08360 live minutesEvaluate costs privacy and human review
70 min explanation · 70 min demonstration · 160 min practice · 60 min review
Evaluate cost privacy and approval constraints
09480 live minutesBuild a small applied-AI capstone
95 min explanation · 95 min demonstration · 215 min practice · 75 min review
Deliver a new bounded applied-AI experiment
10240 live minutesPresent limitations and a reproducible experiment
45 min explanation · 45 min demonstration · 105 min practice · 45 min review
Reproduce the result and explain an unsuccessful case
How you will practise and be assessed.
The planned assessment checks your result, your judgement and your ability to apply what you learned independently.
- 01
Build the promised result
Demonstrate the promised artifact
WHAT YOUR WORK SHOULD SHOWTrain/test separation is justified, baselines are compared and generated outputs are evaluated; no research-model mastery claim.
- 02
Test a limit or failure
Explain generalisation uncertainty and limitations
WHAT YOUR WORK SHOULD SHOWThe documented failure/uncertainty is visible, and no prohibited action or unsupported success claim occurs.
- 03
Apply it independently
Independently explain and change one assumption in a baseline ml exercise and bounded applied-ai prototype.
WHAT YOUR WORK SHOULD SHOWThe learner predicts and verifies the change; AI output is not accepted without understanding.
Where this course stands.
Lab assets and supported tool versions are confirmed before teaching
Explore the source reference- Course ID
- C019
- Content
- Course outline in review
- Trainer
- Instructor to be confirmed
- Enrolment
- Not open · requests welcome
- Publication
- Planned
- Catalogue date
- 2026-10-15
Want to learn this?
Share your interest. We’ll confirm availability, batch dates and the fee separately, so you can decide when the details are ready.
- Your course is already selected
- Just your name and email to get started
- No payment or booking commitment
Know what your batch includes.
Learning support, assessment requirements and any certificate terms are confirmed with the batch before enrolment. Include your goals in your course request so the proposed format can be matched to what you need.
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