Bachelor in Mathematics, Specialisation in Data Science for Artificial Intelligence

3 Years On Campus Bachelors Program

Sorbonne University Abu Dhabi

Program Overview

The Bachelor in Mathematics, Specialisation in Data Science for Artificial Intelligence at Sorbonne University Abu Dhabi is designed for students who enjoy mathematics and want to turn analytical thinking into real-world impact. The programme blends rigorous mathematical theory with modern data science and AI skills, preparing graduates for tech-driven careers or advanced studies.


Curriculum Structure

Year 1:
You’ll build a strong foundation in calculus, linear algebra, probability, and statistics while learning programming in Python. Alongside core mathematics, you’ll begin exploring how data is structured, analysed, and ethically used in artificial intelligence.

Year 2:
The focus shifts to deeper mathematical reasoning and applied data analysis. You’ll study advanced algebra, probability models, and multivariate data analysis, learning how theoretical mathematics powers real data-driven decision-making.

Year 3:
In your final year, you’ll connect theory to practice through statistical inference, optimisation, and machine learning. Advanced data science modules prepare you to design intelligent models and solve complex problems, whether for industry or research.


Focus areas:

Mathematical analysis, probability and statistics, data science, machine learning, optimisation, Python programming.


Learning outcomes:

Graduates develop strong problem-solving and analytical skills, the ability to work with complex datasets, and the confidence to build and interpret AI-driven models in professional or academic settings.


Professional alignment (accreditation):

The programme is officially accredited in the UAE, and the degree is awarded by Sorbonne Université (France), ensuring international academic recognition.


Reputation (employability):

Backed by the Sorbonne’s global reputation in mathematics and science, this degree is well regarded by employers and postgraduate institutions worldwide, particularly in data, AI, and research-focused roles.

Experiential Learning (Research, Projects, Internships etc.)

At Sorbonne University Abu Dhabi, learning goes far beyond the classroom. As a student in this programme, you’ll regularly apply mathematical and data science concepts through practical work, collaborative projects, and exposure to real research environments. You’ll study in a setting where mathematics, AI, and data science are actively explored, giving you early insight into how these skills are used in both industry and academic research.


Your experience is strengthened through dedicated facilities and hands-on opportunities, including:

  • Modern computer labs and digital workspaces where you’ll code, analyse datasets, and work on data-driven assignments.

  • Collaborative group projects that encourage teamwork, problem-solving, and real-world application of mathematical models and data science techniques.

  • Access to AI and data science research centres, allowing motivated students to engage with ongoing research initiatives and explore advanced topics beyond the classroom.

  • Extensive library resources and digital databases to support independent research, coursework, and academic writing.

  • Quiet study areas and collaborative learning spaces designed for focused study, discussions, and project development.

  • Academic support and mentoring, ensuring you’re guided as you transition from foundational concepts to advanced data science and AI applications.

Together, these experiences ensure you graduate with not just strong theoretical knowledge, but the confidence and practical skills needed to succeed in data-driven and AI-focused careers.

Progression & Future Opportunities

Graduates of this programme leave with a powerful mix of mathematical thinking, data analysis, and AI skills that open doors across industries. Many go on to work as Data Scientists or Analysts, Machine Learning Engineers, Statisticians, or Quantitative Analysts, applying their expertise in technology, finance, research, and innovation-driven organisations:

  • Dedicated career support: Sorbonne University Abu Dhabi’s Career & Employability team actively supports students through CV and interview workshops, career coaching, and on-campus recruitment events such as the Astrolabe Career Fair, helping you connect directly with employers and internship providers.

  • Structured career planning tools: Students benefit from digital career-planning platforms that support job exploration, skill mapping, and internship searches throughout the degree.

  • Strong employment outcomes: The university reports that a high proportion of graduates secure employment within months of graduation, reflecting the practical value and international recognition of the degree.

  • Industry and research exposure: Students are encouraged to gain professional experience through internships and applied projects, often working with real datasets or research-driven environments that mirror industry practice.

  • International degree recognition: Awarded by Sorbonne Université and accredited in the UAE, the degree holds long-term value for global employment and further study.


Further Academic Progression:
After completing the bachelor’s degree, many students continue into Master’s programmes in Data Science, Artificial Intelligence, Machine Learning, or Applied Mathematics, either at Sorbonne University Abu Dhabi or at leading universities worldwide. This pathway also prepares strong candidates for research-focused master’s degrees and PhD programmes, making it an excellent foundation for advanced technical or academic careers.

Program Key Stats

AED71,700 (Annual fees)
AED71,700 (Annual fees)
AED 200
Sept Intake : 21st Aug


60 %
Yes

Eligibility Criteria

3
30
80 - 100

750
-
5.5
71
-

Additional Information & Requirements

Country Requirements

Career Options

  • Data Scientist
  • Machine Learning Engineer
  • Artificial Intelligence Engineer
  • Data Analyst
  • Quantitative Analyst
  • Statistician
  • Business Intelligence Analyst
  • Research Scientist (AI/ML)
  • Software Engineer (Data & AI)
  • Actuarial Analyst

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