MS Data Science
Introduction
The MS Data Science at UOR is a two-year professional degree that integrates
advanced data science, computational methods, and analytical decision-making to
address modern economic, business, and industrial challenges. Designed for graduates
and working professionals, the program offers weekend classes (Friday and Saturday),
enabling students to pursue higher education while balancing their professional
commitments. The curriculum equips students with expertise in Big Data, advanced
mathematics, statistical modeling, and computer algorithms to uncover actionable
insights, forecast economic and market trends, optimize business performance, and
solve complex real-world problems. Graduates are prepared to lead data-driven
innovation, support evidence-based policymaking, and contribute to sustainable
economic development across business, finance, industry, government, and research
sectors.
Why choose this course?
Choosing this master’s program at UOR allows you to work at the intersection of
high-level statistics and modern artificial intelligence.
- Access to specialized data labs with powerful servers for processing massive datasets.
- Learning from senior researchers who specialize in predictive modeling and deep learning.
- A curriculum that focuses on the latest tools like Python, R, Spark, and Cloud Analytics.
- Practical exposure through collaboration with local industries for data-driven projects.
- Supportive research environment that encourages the publication of original data models.
Career Opportunities
Graduates of MS Data Science have strong career prospects in multiple
sectors, including technology, finance, healthcare, marketing, and research.
Possible roles include:
- Principal Data Scientist.
- Senior Business Intelligence (BI) Consultant
- Big Data Solutions Engineer
- Lead Data Analyst in Finance or Healthcare
Semesters and Courses
Semester 1
| Course Code |
Course Title |
Credit Hours |
| DS-711 |
Statistical and Mathematical Foundations for Data
Science |
3 |
| DS-712 |
Statistical Computing for Data Science |
3 |
| GEN-700 |
Research Methodology |
3 |
| |
Credit Hours |
9 |
|
Semester 2
| Course Code |
Course Title |
Credit Hours |
| DS-721 |
Econometrics and Regression for Data Science |
3 |
| DS-722 |
Optimization and Numerical Methods for Data Science
|
3 |
| DS-723 |
Statistical Learning for Data Science |
3 |
| GEN-701 |
Understanding of Holy Quran I |
1 |
| |
Credit Hours |
10 |
|
Semester 3
| Course Code |
Course Title |
Credit Hours |
| DS-731 |
Thesis - I / Elective - I |
3 |
| DS-732 |
Time Series Analysis and Forecasting |
3 |
| DS-733 |
Data Mining and Predictive Analytics |
3 |
| GEN-702 |
Understanding of Holy Quran II |
1 |
| |
Credit Hours: |
10 |
Semester 4
| Course Code |
Course Title |
Credit Hours |
| DS-741 |
Thesis - II / Elective - II |
3 |
| |
Credit Hours: |
3 |