Department of

Computer Science and Information Technology

Graduate Program

MS Data Science


With technology existing in a state of constant evolution, the ability to access, understand and analyze data is essential for any organization or company looking to stay ahead of the curve. In our MS / M.Phil. Data Science program, students will learn and develop comprehensive data science skills, including programming, algorithms, machine learning, data mining, parallel and distributed systems, and data management. Over the course of their studies, they will develop a broad base of knowledge with the opportunity to specialize in an area of particular interest.

The MS (DS) program has been designed to give students the option to be part of a data science endeavor that begins with the identification of business processes, determination of data provenance and data ownership, understanding the ecosystem of the business decisions, skill sets and tools that shape the data, making data amenable to analytics, identifying sub-problems, recognizing the technology matrix required for problem resolution, creating incrementally-complex data-driven models and then maintaining them to ultimately leverage them for business growth.

In addition to learning how to use existing statistical and analytical tools for evaluating and interpreting data, students will also learn how to build new tools that facilitate the use of data in making research, policy and business decisions. The learning will be reinforced with practical, hands-on team projects, where you’ll apply your skills to real world problems.


  • The objectives of the M.Phil. Data Science program includes:
    • To equip students to transform data into actionable insights to make complex decisions
    • To enable students to understand and analyze problems and arrive at computable solutions
    • To expose students to the set of technologies that matches 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.


Grand Asian University Sialkot (GAUS) is a modern, demand-driven, futuristic, quality conscious and affordable private university. The University wishes to build its future through internationally recognized research work, scholarship and learning within a distinctive scholarly environment. The vision will inspire GAUS to strive hard in competing globally for better Pakistan based on Knowledge economy characterized by high levels of skills, lifelong learning and innovation.

Eligibility Criteria

A degree of BS (CS) or equivalent as per HEC curriculum, Students with 16 years of education with minimum CGPA of at least 2.0 (on a scale of 4.0) in following domains (Information Technology, Software Engineering, Computer Engineering, Electrical Engineering, Statistics, or Mathematics are eligible to apply provided that they have taken following deficiency courses.

Deficiency Courses:

  1. Programming Fundamentals (Core Programming Course)
  2. Data Structures & Algorithms OR Design & Analysis of Algorithms
  3. Database Systems


The need for data science experts is thriving in every job space and is not limited to technology. Since this is a highly in-demand career choice with high paying salaries, an advanced education coupled with excellent skills is mandatory. 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.

Following are some of the popular data science career tracks that can be pursued by graduates:

  • Business Intelligence Developer
  • Data Architect
  • Applications Architect
  • Infrastructure Architect
  • Enterprise Architect
  • Data Analyst
  • Data Engineer
  • Machine Learning Engineer
  • Statistician

Data science experts are required and valued in almost every field. Many businesses and even governments depend on big data to provide efficient services to their customers. Therefore there is an ever growing demand for a specialized MS/M.Phil. program in Data Science

Scheme Of Studies
MS Data Science

Course Offering Plan

Course Type Number of Courses Cumulative Credits
Program Core courses 3 9
Specialization Requirement Courses 2 6
Electives 3 9
Thesis 6

Core Courses


Title of Course



DSC-611 Statistical and Mathematical Methods for Data Science 3
DSC-612 Tools and Techniques in Data Science 3
DSC-613 Machine Learning 3

Specialization Courses


Title of Course



DSC-621 Natural Language Processing 3
DSC-622 Deep Learning 3
DSC-623 Distributed Data Processing 3
DSC-624 Big Data Analytics 3

Thesis/ Additional Electives

Course Code Title of Course Credits
Thesis (with successful defense) in MS/M Phil (DS)* 6



Title of Course





Thesis-I / Elective Course 3 4
Elective IV 3 4

Thesis/ Electives

Course Code Elective Courses Credits


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