Newspaper adds TUF


Course Facts
Study Level Study Mode Program Duration Credit Hours

Post Graduate


4 Semesters (2 years)


Eligibility Criteria

BSCS/BSSE/BSIT/ Master of Computer Science/Master of informaion Technology/MSc Computer Scicnce with CGPA 2.00/4.00 under semester system or 60% marks under annual system GAT(General)/TUF entry test with 50% marks


• To equip students to transform data into actionable insights to make complex business decisions

• To enable students, understand and analyze a problem and arrive at computable solutions

• To expose students to the set of technologies that match those solutions

• To gain hands-on experience on data-centric tools for statistical analysis, visualization and big data applications at the same rigorous scale as in a practical data science project

• To understand the implications of handling data in terms of data security and business ethics

Role and Scope

The amount of data is growing so rapidly and their significance in the emerging societal set ups such as the pervasive Internet of Things. The way one imagines data is going to change in the coming years. Both Big Data Analytics and pervasive computing hinge on the principle axis of data analytics. MS (DS) program is going to be relevant in terms of job creation and artisanal smart business generation. Graduates from this program would definitely avail the early-bird advantage.

Scheme of studies

Semester 1

Course Code Course Title Credit Hours
DS-711 Statistical and Mathematical Methods for Data Science 3(3+0)
DS-712 Tools and Techniques in Data Science 3(2+1)
DS-713 Data Visualization 3(3+0)
  Credit Hours 9

Semester 2

Course Code Course Title Credit Hours
DS-721 Machine Learning 3(3+0)
DS-722 Big Data Analytics 3(3+0)
DS-723 Deep Learning 3(3+0)
  Credit Hours 9

Semester 3

Course Code Course Title Credit Hours
DS-731 MS Thesis-I 3(0+3)
DS-732 Social Network Analysis 3(3+0)
  Credit Hours 6

Semester 4

Course Code Course Title Credit Hours
DS-741 MS Thesis-II 3(0+3)
DS-742 Time Series Analysis and Prediction 3(3+0)
  Credit Hours 6
Total Credit Hours 30