The best way to make the modules stick is to build something. These five projects take you from an Excel dashboard through a SQL analytics project, exploratory data analysis in Python, a Power BI dashboard, and finally A/B testing in Python.
Each one is a code-along video, so you can pause, work through it yourself and adapt it to your own ideas. Pick the project that matches the module you've just finished and come back for the rest.
Once you've followed along, repeat the project with a public dataset you care about, then publish it on GitHub or a portfolio site: finished projects are what hiring managers look at.
Turn raw sales data into a dashboard with PivotTable KPIs, trend and category charts, slicers and a timeline filter, a hands-on drill for the spreadsheets module.
Work through a full SQL project: changes over time, cumulative and performance analysis, part-to-whole and segmentation, then build customer and product reports.
Clean and explore a large real-world dataset in a Jupyter notebook using pandas and Seaborn, from first look to patterns and outliers.
Load and model sample data in Power BI, then build a sales dashboard with KPI cards, a heatmap and clear bar charts.
Frame a hypothesis, run an A/B test in Python, interpret the results and avoid the common pitfalls.