Cohort-based, hands-on programmes taught by lecturers and working data scientists — with real datasets, live projects, and certificates that mean something.
An intensive, applied training that takes you from spreadsheet basics to real analytics: data wrangling, visualization, statistical inference, and an introduction to machine learning — built around the tools employers actually use.
Secure instant enrolment with M-Pesa STK push — you’ll receive a prompt on your phone the moment you register.
| Wk | Module | Key topics |
|---|---|---|
| 1 | Foundations | The data analytics lifecycle, tools setup, Python & Jupyter, data careers in Africa |
| 2 | Working with Data | Data types, spreadsheets to code, importing, cleaning, and structuring datasets |
| 3 | Data Wrangling | Pandas DataFrames, missing data, transformations, feature preparation |
| 4 | Visualization & EDA | Charts that communicate, exploratory analysis, correlation, dashboards |
| 5 | Statistical Inference | Hypothesis testing, t-tests, chi-square, ANOVA — drawing defensible conclusions |
| 6 | Intro to Machine Learning | Regression and classification, model evaluation, avoiding common pitfalls |
| 7 | Capstone & Showcase | End-to-end project on a real dataset, presentation, certification |
Our flagship applied programme — from Python foundations through machine learning, neural networks, and generative AI, capped with a GitHub portfolio capstone.
Big Data Analytics (Spark, cloud platforms) · R for Statistical Research · STATA for Econometrics · Advanced ML & AI with MLOps.
