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BDS: Programme structure


A 21st century curriculum to help you excel as a global leader

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Our programme curriculum is benchmarked against the world's best universities, developing competitive graduates.

Curriculum summary

Data Scientists have revolutionized how we analyse big data and the way organisations identify trends and challenges as well as new opportunities. This demonstrates that big data offers enormous social and economic benefits. The BSc in Data Science equips students with the knowledge, understanding and skills to conduct data-driven investigations and visual and advanced analytics by acquiring and managing data of all types. Data Scientists need to be curious to identify new trends, have an expertise in mathematics and technical skills to craft solutions, and business acumen to make strategic decisions based on data-driven results.

Students will develop an in-depth understanding of data science and the techniques for analysis of quantitative and qualitative data to arrive at solutions. They will learn how the strategic use of big data can provide competitive advantage - underpinning new waves of productivity growth, innovation and consumer surplus.

Students will acquire a core mathematical knowledge upon which they will build competences in computation, optimal decision making, probabilistic modelling, and statistical inference. By learning the theory behind data science, students will develop the capacity to stay up-to-date in a field that is evolving rapidly. A unique feature of the course is the requirement to undertake a final year, applied analytics capstone project that give students practical, hands-on experience in identifying and interpreting actionable information from raw data, and using them to make informed, mathematically valid decisions.

After completion of year 2 taught modules, students will engage in work-based learning via a 4- month (16 week) pass / fail internship*. This can be undertaken either in the UK or in Singapore, subject to visa requirements. This allows the student to gain first-hand experience within a real business environment to enhance their future employability. Students work on an agreed project relevant to their degree, with support from both a corporate and academic mentor. At the end of the internship* students will submit a report which includes a critical reflection of their workplace experience and a final presentation.

Note: We do not guarantee internships.

Programme Aims
  • To provide students with knowledge of the fundamental principles and technologies that underpin the disciplines of mathematics, statistics and computing with an emphasis on the skills and theories required in data science and analytics.
  • To provide practical skills of applied data science and business analytics to inform strategic, commercial and policy decisions.
  • To prepare students with professional attitudes with awareness of ethical, legal, and social issues, interpersonal and entrepreneurial skills required in industry.
  • To equip students with a combination of analytical, technical and presentation skills needed to convert data into valuable insights in an appropriate format to support decision making.
  • To prepare students for continued study at an advanced level in either formal postgraduate study or as continued professional development.

Programme Structure

Students must earn 360 credits to fulfil the requirements of the 3-year BDS programme. Credits are a way of measuring the amount of academic work you complete as part of your degree programme. You gain credits for each module you complete. Each credit represents the successful completion of a module's learning outcomes and requirements. To learn more about credits and how they contribute to your degree, please click here.

Core subjects




Minor Project




Major Project











As a BDS student at SPJ London, you can expect a higher level of engagement with the curriculum, with 18 contact hours per week, compared to the average of 12 hours per week in UK business schools. Contact hours refer to the time you spend in face-to-face teaching sessions with our expert academic staff, giving you ample opportunities to deepen your understanding of the subjects, ask questions, and participate in lively discussions.

Note: We do not guarantee internships.


Programme Intended Learning Outcomes


On successful completion of the named award, students will be able to:

  • Demonstrate understanding of data science and the theories that underpin it.
  • Interpret and apply advanced quantitative techniques to the analysis of large and complex data.
  • Demonstrate good knowledge and understanding in advanced areas of statistics.
  • Evaluate and apply data modelling methods and interpret descriptive and referential statistics for various quantitative data.
  • Systematically understand and appreciate the importance of ethical behavior, negotiation, effective work habits, leadership and good communication with stakeholders.


On successful completion of the named award, students will be able to:

  • Apply problem solving, decision making and critical thinking skills to evaluate and arrive at clear, reliable, well-structured solutions from the analysis of data.
  • Critically assess the relative merits of quantitative methodologies and use them appropriately for the problem in hand.
  • Communicate and collaborate effectively with others to design programs and apply various data analysis methodologies to data sets, as well as prepare and communicate output, implications, and solutions to all stakeholders.


On successful completion of the named award, students will be able to:

  • Communicate effectively in a written context.
  • Use information technology (spreadsheets, word processing, online databases and AI technology, such as ChatGPT) appropriately.
  • Organise information, assimilate and critically evaluate competing arguments and methods.
  • Manage their own learning by working effectively to deadlines.
  • Be open minded and have a capacity to handle ideas and scrutinise information in ethical and analytical ways.


On successful completion of the named award, students will be able to:

  • Systematically understand, apply and explain the ethical and privacy implications of managing (big) data.
  • Appreciate and apply theoretical and technical knowledge and skills to provide socially and ethically responsible data solutions with accountability.
  • Critically assess the broader impact of data science on society and the principles of fairness, accountability and transparency and shared ethical values.
  • Collaborate responsibly with others to produce deliverables that are appropriate for audiences of different socio-economic groups and for different businesses.

Teaching, Learning and Assessment Methods

Today’s agile employment sector requires flexible, job-ready business graduates with both professional and academic experience. The range of learning and assessment methods in SPJ London programmes are designed to prepare you for this, ensuring maximum employment potential as soon as you graduate.

Experiential Learning
We encourage critical analysis and debate on contemporary management issues and place emphasis on independent study and research. At the core of our programmes is the belief that learning should reflect real life business contexts. Students thrive where theory meets practice, which is why our courses emphasize interactive elements such as business simulations, live projects, real time trading, seminars and rich industry-academic collaborations.


SPJ London’s applied-learning approach to assessment ensures you graduate with practical, immediately applicable skills. Continuous assessment through individual and group assignments, class participation, simulations, projects, and examinations accurately quantifies your understanding and growth. Our assessments are ‘authentic’ - designed to mimic real world environments.


Global Learning
The SP Jain global experience goes beyond the four walls of the classroom. In each of the cities, students participate in structured global immersion activities that expose them to regional business practices, political beliefs and cultures. For instance, in Dubai, students visit the Burj Khalifa to understand the strategic planning behind its creation. London too will host its own set of cultural immersion experiences. This distinctive aspect of our multi-campus learning model ensures that students acquire academic knowledge but emerge as culturally enriched global graduates.



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