Data Science: Statistics, Modelling and Experimentation

Turn data into predictions and decisions with Python, statistics and rigorous experiments.

A university-level data science course covering the full workflow: framing questions, wrangling data in Python, statistics and probability, exploratory analysis, predictive modelling with scikit-learn, experimentation and A/B testing, and communicating results to decision makers.

120h 2 certificates available

Data SciencePythonStatisticsscikit-learnExperimentation

Curriculum

Two complete tracks. Study either or both — each has its own exam and certificate.

Eight modules from problem framing and Python data wrangling through statistics, modelling, experimentation and stakeholder communication.

How real projects run, from question to decision.

Framing Questions and Success Metrics Lab40 min
The CRISP-DM Lifecycle in Practice Lab40 min
Data Sources, Ethics and Bias Lab40 min
Notebooks, Environments and Reproducibility Lab40 min

Careers this prepares you for

Data Scientist
Product Analyst
Quantitative Analyst
Research Scientist
Decision Scientist

How you study

Every lesson pairs an in-depth video with written notes, key takeaways, a hands-on lab, exercises and a quiz. Work at your own pace, then sit the final examination for your Erudex certificate.

Data Science: Statistics, Modelling and Experimentation

Curriculum

Module 1Module 1 — The Data Science Workflow

Module 2Module 2 — Python for Data Work

Module 3Module 3 — Probability and Distributions

Module 4Module 4 — Statistical Inference

Module 5Module 5 — Exploratory Analysis and Visualisation

Module 6Module 6 — Supervised Learning

Module 7Module 7 — Unsupervised Learning and Time Series

Module 8Module 8 — Experimentation and Delivery

Careers this prepares you for

How you study