Data Analytics

Turn raw data into decisions

Python, NumPy and Pandas for wrangling; Matplotlib and Seaborn for seeing; statistics and EDA for reasoning; SQL, Excel, Power BI and Tableau for the business.

5 stages · 10 topics · 64 lessons

Stage 1: Python for Data

Python basics through files, exceptions and OOP.

1 topic

Up next · Stage 02Python alone is slow for data. Move to arrays and DataFrames.

Stage 2: Data Manipulation

NumPy arrays and Pandas DataFrames.

2 topics

Up next · Stage 03Clean data is only useful once you can see it.

Stage 3: Data Visualisation

Charts that answer questions.

2 topics

Up next · Stage 04Combine statistics with charts to explore a dataset properly.

Stage 4: Statistics & EDA

Describe a dataset, then explore it end to end.

2 topics

Up next · Stage 05Most business data lives in databases and spreadsheets. Learn to work there too.

Stage 5: SQL, Excel & BI

Query where the data lives; present it where decisions are made.

3 topics

Final stage: Build your portfolio

Real projects built with the skills on this roadmap.

See how this roadmap connects to the othersThe interdisciplinary map shows every roadmap as a line, with shared topics as interchanges.Open the map