Bachelor of Science in the Mathematics of Data Science
Critical sectors of the economy and whole fields of inquiry have been transformed, as the availability of data at unprecedented scale has made it possible to solve daunting problems, that were previously inaccessible. This data revolution has fueled a meteoric rise in the demand for data scientists, with advanced analytical skills, who can transform data into knowledge and business insights. The Mathematics of Data Science program is designed to address the increasing talent gap in data science and train the next generation of highly skilled data scientists with the knowledge and domain expertise needed to thrive in a data-driven economy. The Mathematics of Data Science program will be hosted by the Department of Mathematical Sciences, COS. The program emphasizes the integration of the three pillars of data science – computational, and mathematical thinking – into a cohesive transdisciplinary course of study and internship experience in data analytics. The gained knowledge will introduce students to the concepts, tools, and methods to collect, process, and analyze data. Students will develop the ability to uncover hidden patterns and gain useful insights to solve real-world problems. The emphasis on developing and solving real-world problems in the relevant domain, two distinctive features of the program, will enable students to gain a comprehensive and fully integrated literacy in the foundational areas of data science and artificial intelligence and develop expertise in their domain of interest. Armed with these skills, students will develop the ability to use data and methodically connect theory to problems in hand to derive effective solutions to these problems in the context of the domain under consideration. Although a large demand for data science skills comes from high-tech companies, recent reports show that sectors other than technology are facing a noticeable shortage of skilled data scientists. The graduates of the program will gain the core skills and domain expertise to successfully compete for leading-edge jobs in all sectors of the economy.
Program Objectives
- Contribute to the growth of a UAE task force that excels on the global stage through the application of critical thinking. Proficiency in mathematics and data science is essential to address the requirements of UAE government agencies and align with market demands.
- Elevate the mathematical data science capabilities of the UAE to a level of depth and breadth necessary for leadership across diverse application domains and career sectors vital to the entire economy.
- Create skilled graduates with strong mathematical data science foundations, lifelong learning commitment, effective communication, risk assessment, and teamwork abilities.
- Demonstrate ethical professionalism in accordance with societal norms, while prioritizing environmental awareness.
- Develop strong mathematical skills and practical experience to succeed in the changing world of data science, helping the UAE's economy grow and stay sustainable.
Program Learning Outcomes
Upon successful completion of this program, students will be able to:
- Identify, formulate and solve complex problems by applying knowledge of mathematics and data science.
- Formulate or design a mathematical model, procedure or algorithm for real-life data science problems, in a wide range of application domains.
- Communicate effectively mathematical ideas related to data science problems through presentations and reports to a range of audiences.
- Search literature to understand ethics and professional responsibilities, and the impact of mathematical data science solutions in different contexts.
- Work effectively in teams to accomplish common goals, plan tasks, meet deadlines, and analyze risk and uncertainty.
- Utilize data, apply clear and well-organized mathematical reasoning, and employ data science principles, methods, and techniques to help solve problems and draw meaningful conclusions.
Degree Requirements
Required Credit Hours :
minimum 120 hours
General Education (Req. CH:33)
Cluster 1: Skills for the Future (Req. Ch:15)
| Area 5: Quantitative Reasoning (3 hours
)
| Credit Hours |
|---|
| MATH105 | Calculus I 2 | 3 |
2 : Also counts towards the Major |
Cluster 2: The Human Community (Req. Ch:12)
| Area 2: Social and Behavioral Sciences (3 hours
)
| Credit Hours |
|---|
| PSYC313 | Educational Psychology 3 | 3 |
3 : Also counts towards the Major |
Cluster 3: The Natural World (Req. Ch:6)
Foundation Requirements (42 CH)
Mathematics of Data Science (21 CH)
Elective Courses (24 CH)
