Objectives
- Explore and prepare data with Python
- Train and evaluate machine learning models
- Explain a model's predictions
- Put a model into production
Curriculum
- Scientific Python (pandas, NumPy)28 h
- Statistics & probability24 h
- Supervised machine learning36 h
- Unsupervised & time series28 h
- Explainability & ethics16 h
- MLOps & final project48 h
Audience & prerequisites
Audience: Analysts, statisticians and engineers who want to master machine learning.
Prerequisites: Basic statistics, some Python.
Tools used
Pythonscikit-learnJupyterMLflow
Assessment and certification
The programme ends with a practical project assessed by a panel of practitioners. Passing it earns the Africa Data Entry certificate « Data Scientist ».
Enrolment
An advisor will contact you within 48 hours to confirm your enrolment and funding.