Bachelor's in Data Science
An undergraduate degree, usually three or four years after secondary school, that gives you a broad grounding in a field before you specialise, go on to a master's or start work.
Overview
Why study a Bachelor's in Data Science?
A bachelor's in Data Science is a first degree that trains you to work with data from the ground up: programming, statistics, databases and machine learning, taught together rather than as separate subjects. You enter it straight from school, usually with Class 12 mathematics or its equivalent. Some universities offer it as a single-subject degree, while others combine it with mathematics, statistics, economics or computer science, or run it as a major within a broader science or IT degree. The balance between statistics and computing varies, so compare module lists before applying.
The first year concentrates on foundations: calculus and linear algebra, probability, an introduction to programming in Python or R, and basic data handling. In the second year you move on to statistical modelling, machine learning, databases and visualisation, often with a group project on a real dataset. The final year usually brings options such as deep learning, natural language processing or big data systems, together with an individual project. Degree length depends on the country, from three years in England and Australia to four in North America and Scotland.
Practical experience counts for a lot in this field. Look for programmes with built-in work experience: a sandwich year with an employer is a common option in the UK, co-op terms are widespread in Canada, and in the United States students usually seek summer internships. Students who enter data competitions, contribute to open-source tools or publish small analyses online give themselves something concrete to discuss in interviews. A bachelor's prepares you for analyst and junior data roles, and some graduates later take a master's to move into more specialised modelling work.
Curriculum
What you may study
Across three or four years, a Data Science bachelor's commonly includes topics such as these.
- Calculus, linear algebra and optimisation
- Probability and statistical inference
- Programming in Python and R
- Databases and SQL
- Data cleaning and exploratory analysis
- Regression and statistical modelling
- Machine learning fundamentals
- Data visualisation and storytelling
- Data ethics, privacy and governance
- Final-year data project
Published programmes for Data Science at Bachelor's
No programmes for Data Science at Bachelor's are published yet.
Not in our catalogue yet: that reflects what Universta lists, not what universities teach.
Programmes show each university’s published offering. Course guides describe the course across universities.
Admission
Getting into Bachelor's in Data Science
The usual entry route is Class 12, or another recognised school-leaving certificate, with good overall marks, and mathematics is nearly always required, often at a specified minimum. Some prefer applicants who also studied computer science, statistics or physics, while a few accept commerce students who took mathematics. Required marks differ between universities and school boards, so confirm the figure on every course page. In the United States your whole application is weighed, including essays, teacher recommendations and activities outside class, and test policies on the SAT and ACT vary.
Most universities ask for an English test such as IELTS, TOEFL or PTE, and some waive it for students with a high English score in Class 12 from particular boards, so check the waiver rules. In the UK you apply through UCAS, in the United States often through the Common App or a university's own system, and in Canada and Australia either directly or through a provincial or state admissions centre. Data science bachelor's study in Germany is mostly in German, and Indian school-leavers generally need a Studienkolleg or some university study at home first; the DAAD admission database explains the rules.
Careers
Career pathways
Data Science bachelor's graduates typically begin in positions like the following, with more senior modelling work usually following experience.
- Data Analyst
- Junior Data Scientist
- Business Intelligence Analyst
- Data Engineer
- Analytics Engineer
- Product Analyst
- Marketing Analyst
- Credit Risk Analyst
- Supply Chain Analyst
- Insight Analyst
- Reporting Analyst
- Data Quality Analyst
Sectors
Industries
Retail and E-commerce
Graduates analyse sales, pricing and customer behaviour, build dashboards for merchandising teams and help run online experiments.
Financial Services and FinTech
Lenders, insurance companies and payment providers recruit graduates as analysts in credit risk, fraud monitoring and customer analytics, often through structured graduate programmes.
IT Services and Consulting
Consultancies hire graduates into data and analytics practices, where they build reports, data pipelines and simple models for client organisations.
Software and Cloud Services
Product companies employ graduates as product or data analysts who track how features are used and support decisions with evidence.
Telecommunications and Networks
Operators use junior analysts to study network usage, predict which customers may leave and help plan capacity.
Public Sector and Digital Government
Government departments and statistics offices recruit graduates to work on official statistics, service data and policy analysis.
Who hires
Employers
- Amazon
- Deloitte
- Accenture
- JPMorgan Chase
- Unilever
- SAP
- Tata Consultancy Services
- Infosys
- Flipkart
- Mu Sigma
Named for illustration only; not a ranking, endorsement or partnership.
Outlook
Looking ahead
Generative AI tools can now write SQL, produce charts and draft an analysis from a plain-language request, which takes some routine reporting off a junior analyst's desk. That puts more weight on what the tools cannot do reliably: deciding which question is worth answering, checking whether the data supports the answer and spotting when a result is wrong. Graduates who understand the statistics underneath the software, rather than only the buttons to press, are best placed as these tools spread.
Data roles are also becoming more specialised. Analytics engineering, data engineering and machine learning operations have grown into distinct jobs, and regulation on personal data and AI in Europe, India and elsewhere is raising demand for people who can handle data responsibly. Choosing options in cloud data platforms, privacy or a domain such as health or finance can help a bachelor's graduate stand out as the field changes.
Specializations
Other Computing & Information Technology specializations at Bachelor's
Subject
Computing & Information Technology at Bachelor's
Questions
Questions about Bachelor's in Data Science
Is a Data Science bachelor's better than Computer Science for data jobs?
Not necessarily. A Data Science degree gives you more statistics and applied modelling early on, while Computer Science gives deeper programming and systems knowledge, which suits data engineering and machine learning engineering. Graduates of both reach data roles. Choose the one whose modules you would enjoy more over three or four years.
Can I apply for a Data Science bachelor's with commerce in Class 12?
Possibly, if you took mathematics in Class 11 and 12. Most Data Science bachelor's degrees require school mathematics, and some ask for a high mark in it, so commerce students without mathematics usually need a foundation year first. Check each university's subject requirements.
Does a Data Science bachelor's lead straight to a data scientist job?
Sometimes, but more graduates start as data analysts, business intelligence analysts or junior data engineers, then move into data scientist roles after a year or two of experience or a master's. Internships and a strong project portfolio make a direct move more likely.
How much coding is there in the first year?
Usually a steady amount. Most programmes teach Python or R from the first weeks, with weekly exercises and small projects, and add SQL soon after. No previous experience is normally assumed, but practising basic programming before you start makes the first term less intense.
Plan
Plan your Bachelor's
Keep exploring
More on Data Science
Next step
Planning Bachelor's in Data Science?
Tell us about your academic profile, goals and budget to explore your options.
Free assessmentPersonalised guidanceNo obligation