Primary → PhD

Data Science & Analytics

Descriptive statistics, data cleaning, visualisation choice (bar, line, pie, scatter, histogram, box plot), probability, correlation & regression, hypothesis testing, dashboards, Python/pandas analysis, machine learning basics — school through Masters level

Analyse your own data right here

Upload a CSV or Excel file, or type your figures in by hand. Data Studio describes every column, works out the statistics and recommends the best chart — then draws it in colour.

Open Data Studio

Try an example

  • 1I have monthly sales for 3 regions — which chart should I use and why?
  • 2Find the mean, median, standard deviation and outliers in this dataset
  • 3Explain when to use a pie chart instead of a bar chart
Solve one of these

Pick your level

Each level uses the right language and depth for where you are studying. Select a level to see whatdata science support looks like.

Primary school learners and beginners

Primary / Beginner

Very simple language and small, explicit steps — perfect for primary school and first-time learners.

Junior and senior secondary students

Junior / Secondary

Standard school notation and moderate detail — ideal for junior and senior secondary students.

Senior secondary and high-school students

Senior Secondary / Advanced

Formal notation and efficient reasoning — for advanced secondary, high-school exams and college prep.

University undergraduates

University / Undergraduate

Rigorous university-level reasoning with assumptions, laws and theorems named clearly.

Professionals and certification candidates

Professional / Certification

Industry-ready answers, standards, frameworks and real-world best practice for certifications.

Masters and postgraduate students

Masters / Postgraduate

Postgraduate rigour: full derivations, code clauses, limitations and alternative advanced methods.

PhD researchers and academics

PhD / Research

Doctoral research rigour: formal proofs, literature comparison, complexity analysis and future directions.

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