PROGRAM LEVEL
The Bachelor of Science in Statistics and Data Science was constructed on a multidisciplinary basis that integrates statistics with mathematical foundation and computer science at the aim of acquiring graduates with a wide spectrum of highly demanded skills in the data-world economy.
The program consists of 133 credit hours balance theory with practice to prepare students for the workforce directly after graduation.
The theoretical foundation is stemmed from statistics, mathematics, and computer science, while the practical experience is represented by the domain-specific applications which are covered through course projects, senior research project, and internship.
Moreover, students will be exposed to technologies, data analysis techniques, and different software to handle and analyze data appropriately to find solutions for real-world problems in different domain-specific fields. Furthermore, students will learn how to work effectively as part of a team and communicate the resulting outcomes to stimulate the work environment.
Finally, the Bachelor of Science in Statistics and Data Science program has been placed at level 8 in the NQF in 2025.
ABOUT THE PROGRAM
DETAILED STUDY PLAN
- Press here to download the Academic Plan of the program 2025 Â Â (PDF, 0.9 MB , 18 Pages)
- Press here to download the Academic Plan of the program 2021 Â Â (PDF, 1.0 MB , 19 Pages)
PROGRAM OBJECTIVES
- Work successfully as statistician and data scientist to address problems of data-related careers.
- Engage in research activities, graduate and professional studies in data-related domains.
- Enhance society development through effective use of data-based knowledge and skills.
PROGRAM INTENDED LEARNING OUTCOMES
Upon successful completion of the bachelor degree in statistics and data science, the graduates will be able to graduation, an UOB graduate in mathematics should be able to:
- Explain mathematical concepts and principles of basic sciences underlying statistical and computational methods.
- Operate effectively with multiple-source and multiple-format data for all stages of the data science process.
- Integrate data privacy, legal and ethical issues within professional practice.
- Formulate a problem of interest by a statistical model taking into consideration the underlying assumptions.
- Validate problem-specific models using statistical or machine learning methods to draw data-driven decisions.
- Perform computational tasks that can be executed with professional programming software and appropriate problem-solving algorithms.
- Communicate effectively through written reports or oral presentations.
- Engage with research and lifelong learning activities in the field of statistics and data science.
