Statistics for Data Science Course
Master core statistics for data science using real student analytics. Clean data, summarize distributions, run correlations and hypothesis tests, and turn results into clear, ethical, evidence-based recommendations stakeholders can act on.

4 to 360 hours of flexible workload
valid certificate in your country
What Will I Learn?
This short, practical course builds your ability to clean learning data, summarize key metrics, and visualize distributions for clear comparisons. You will compute robust summaries, correlations, and effect sizes, run appropriate hypothesis tests, and create polished plots in Python or R. Finish ready to deliver concise, reproducible reports, actionable recommendations, and ethical insights for data-driven course decisions.
Elevify Differentials
Develop Skills
- Data cleaning for student analytics: fix errors, outliers, and missing data fast.
- Descriptive stats mastery: compute, compare, and interpret key course metrics.
- Distribution and correlation analysis: reveal patterns with ECDFs and robust plots.
- Hypothesis testing for education data: pick the right test and report clear effects.
- Insight communication: turn stats into concise, ethical, action-ready reports.
Suggested Summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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