MS Computing and Data Sciences
Apply now →Program Overview
The MS Computing and Data Sciences at TUF is a two-year professional degree that turns students into experts at handling "Big Data." In this program, you learn how to use advanced mathematics and computer algorithms to predict future trends and solve complex industrial problems. It is designed for those who want to lead the digital transformation in business, science, and government sectors.
Why choose MS Computing and Data Sciences at TUF?
Choosing this master’s program at TUF 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.
Key Skills You Will Master
Data Mining
Machine Learning
Statistical Modeling
Big Data Processing
Research Methodology
Data Visualization
Career Outcomes
Graduates of MS Computing and Data Sciences have strong career prospects in multiple sectors, including technology, finance, healthcare, marketing, and research. Possible roles include:
- Principal Data Scientist
- Machine Learning Architect
- Senior Business Intelligence (BI) Consultant
- Big Data Solutions Engineer
- Lead Data Analyst in Finance or Healthcare
Program Roadmap
Explore courses roadmap in MS Computing and Data Sciences
| Course Code | Course Title | Credit Hours | Category | Prerequisite |
|---|---|---|---|---|
| DS-711 | STATISTICAL AND MATHEMATICAL METHODS DATA SCIENCE | 3 (3-0) | - | - |
| DS-712 | TOOLS AND TECHNIQUES IN DATA SCIENCE | 3 (2-1) | - | - |
| DS-713 | DATA VISUALIZATION | 3 (3-0) | - | - |
| Course Code | Course Title | Credit Hours | Category | Prerequisite |
|---|---|---|---|---|
| DS-721 | MACHINE LEARNING | 3 (3-0) | - | - |
| DS-722 | BIG DATA ANALYTICS | 3 (3-0) | - | - |
| DS-723 | DEEP LEARNING | 3 (3-0) | - | - |
| Course Code | Course Title | Credit Hours | Category | Prerequisite |
|---|---|---|---|---|
| DS-731 | MS THESIS I | 3 (0-3) | - | - |
| DS-732 | SOCIAL NETWORK ANALYSIS | 3 (3-0) | - | - |
| Course Code | Course Title | Credit Hours | Category | Prerequisite |
|---|---|---|---|---|
| DS-741 | MS THESIS II | 3 (0-3) | - | - |
| DS-742 | TIME SERIES ANALYSIS AND PREDICTION | 3 (3-0) | - | - |
Admissions & Eligibility
BSCS/BSSE/BSIT/ Master of Computer Science/Master of lnformation Technology/MSc Computer Science with CGPA 2.00/4.00 under semester system or 60% marks under annual system. GAT(General)TUF entry test with 50% marks