Data analysis

Data analysis tutoring, on your own data

Real analysis is learned on messy data, not toy examples. Bring the spreadsheet, dataset or dissertation results you are actually working with and we work through it together: cleaning, exploring, choosing a method, and explaining what the output means.

Tools you can learn

• Excel: Formulas, pivot tables, lookups, cleaning and what-if analysis.
• Google Sheets: Shared workbooks, query functions and lightweight automation.
• Python: pandas and NumPy for cleaning, joining and analysing real datasets.
• R: Statistical analysis and reproducible reporting, including R Markdown.
• SQL: Selecting, filtering, joining and aggregating data in a real database.
• Tableau and Power BI: Dashboards that show the finding rather than decorating it.
• Jupyter: Notebooks that keep your analysis, notes and results together.

Who it is for

• Students analysing survey, lab or field data for a project.
• Dissertation and thesis writers who need to clean, test and explain their data.
• Professionals who inherited a spreadsheet and want to trust it.
• Career changers building practical skills for data-focused roles.

Session formats

• Live 1-on-1: Screen-shared sessions working directly on your data.
• Recorded lessons: Walkthroughs you can revisit while you work.
• Project reviews: Feedback on an analysis you have already started.

What you can expect to be able to do

Every session targets a capability rather than a promise: clean and document a dataset, choose an appropriate method, run the analysis yourself, sanity-check the output, and write up findings in plain language. We do not publish invented results or grades.

Related subjects

Ready to start?

Send a request with the tool you are using and what you are trying to find out.