Computing & Mathematics
Data Science
数据科学
Data Science connects statistics, data cleaning, visualisation. Study combines ideas with practical work, analysis and discussion; the exact curriculum varies by institution.
See a small experiment ↓
What you’ll explore
- Statistics
- Data cleaning
- Visualisation
- Machine learning
A sample assignment: Explain a pattern in a public dataset with two charts.
The reality behind the title
Debugging and abstract problems can involve long periods without an obvious answer.
Useful preparation: Mathematics, computing, clear written reasoning.
These are general suggestions, not admissions requirements.
Subject-focused universities & programmes
Selected for this subject’s curriculum and training routes. Read what makes each example useful, then compare the official programme. Related degrees and concentrations are labelled.
- University of California, Berkeley United StatesData Science, BA ↗
Undergraduate degree
Combines computing, statistics and application domains in an interdisciplinary major.
Official listing checked 2026-10-27 - Carnegie Mellon University United StatesStatistics and Machine Learning, BS ↗
Undergraduate degree
A statistics-and-machine-learning route for comparing the mathematical depth behind data work.
Official listing checked 2026-10-27 - University College London United KingdomData Science BSc ↗
Undergraduate degree; see the official award above
A directly named Data Science BSc to compare with Berkeley’s BA and CMU’s statistics-and-ML degree.
Official listing checked 2026-10-27
Where it might lead
Examples to explore, not guaranteed jobs. Skills, location, experience and qualifications affect entry.
- Data analyst
Apply statistics to practical problems; build a small project and look for supervised entry-level experience.
Possible settings: industry teams, consultancies, public organisations and research groups.
- Data engineer
Use data cleaning to evaluate options and explain findings to others; practise research and clear communication.
Possible settings: industry teams, consultancies, public organisations and research groups.
- Analytics researcher
Pursue a research or professional training route. Independent research and regulated practice often require further study and specific qualifications.
Possible settings: industry teams, consultancies, public organisations and research groups.
Experience before deciding
Explain a pattern in a public dataset with two charts
About 90 minutes of active work, within seven days of starting.
- Spend 20 minutes learning the basics of statistics from an official university course or open educational resource.
- Explain a pattern in a public dataset with two charts
- Ask a willing peer for feedback, then record one engaging part, one difficulty and one question.
Output: One page or small prototype showing your method, result and limitations.
Use public examples or a paper simulation if tools, interviews or equipment are unavailable. No spending is required.
You can read the activity freely. Sign in to start and save it.
Nearby possibilities
Sources & content notes
University links above are official programme listings checked on 27 October 2026. Descriptions and experiments are editorial summaries, not quotations or university advice. Course structure and admissions requirements can change. Images are AI-generated concept illustrations.