Machine Learning Foundations for Professionals
Understand how machine learning models are built, tested and deployed, and work hands-on with real datasets in Python.
- 5 days
- Classroom · Live virtual · In-house
- Afriskora Certificate of Completion
Course overview
Many organisations buy AI tools without anyone inside who understands how the models behind them learn, fail or drift. This course takes analysts, engineers and technical managers from first principles to a working model: preparing data, choosing an algorithm, measuring accuracy honestly and explaining results to decision-makers. Exercises use public African datasets from agriculture, health and finance, and no advanced mathematics is assumed.
Who should attend
- Data and business analysts moving into machine learning
- Engineers and IT professionals supporting AI projects
- Technical managers who oversee data science teams
- Researchers and statisticians modernising their toolkit
What you will be able to do
- Explain supervised, unsupervised and generative learning in practical terms
- Prepare and clean data so that models learn the right patterns
- Train, tune and compare models in Python with scikit-learn
- Measure model performance and spot overfitting, bias and drift
- Plan how a model moves from notebook to production safely
Course outline
Day 1Machine learning in context
- • Where machine learning fits alongside rules and statistics
- • The model life cycle from question to deployment
- • Python, notebooks and core libraries
- • Framing a business problem as a learning task
Day 2Data preparation
- • Exploring and profiling a dataset
- • Handling missing values, outliers and imbalance
- • Feature engineering and encoding
- • Train, validation and test splits
Day 3Supervised learning
- • Regression for forecasting quantities
- • Classification with trees, ensembles and logistic models
- • Hyperparameter tuning and cross-validation
- • Choosing the right metric for the decision
Day 4Unsupervised and generative methods
- • Clustering customers, assets and transactions
- • Anomaly detection for fraud and faults
- • How large language models and embeddings work
- • When to use a pre-trained model instead of building one
Day 5Responsible deployment
- • Explainability and communicating results
- • Fairness, bias testing and data protection
- • Monitoring for drift after go-live
- • Capstone: present a model to a mock steering committee
Frequently asked questions
How long is the Machine Learning Foundations for Professionals course?
The course runs for 5 days. Daily start and finish times are confirmed in your joining instructions. Live virtual sessions cover the same programme.
Do I receive a certificate?
Yes. Every participant who completes the course receives an Afriskora Certificate of Completion with a unique code that employers can verify online.
Can this course be delivered in-house for our team?
Yes. We can run it at your premises or online for your team, on dates that suit you, and adapt examples and case studies to your sector.
How do I book and pay?
Request dates and we'll send available sessions and a quote. Bookings are confirmed by invoice and paid by EFT. South African clients can include the course in their Workplace Skills Plan.
Related courses
Generative AI at Work
Use ChatGPT, Copilot and other generative AI tools safely and productively for writing, analysis and everyday tasks.
3 daysAI for Business Leaders
Understand where artificial intelligence creates value, how to lead AI projects and how to manage the risks.
3 daysData Analysis with Python
Learn Python from the ground up to clean, analyse and visualise data, no programming background required.
5 days