UNIVERSITY OF MANAGEMENT AND TECHNOLOGY

Academic Programs

Computing & Data Science Program

Overview Road Map

Program Introduction

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. 

Program Objectives

The program in computing & data science has been designed to produce a stream of future data scientists and professionals with the following objectives:

  • To equip students to transform data into actionable insights to make complex business decisions.
  • To enable students, understand and analyse 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.

Career Opportunities

MS degree program in Software Engineering at UMT provide students with the comprehensive skills and knowledge they need to pursue the best career option in one of the most dynamic areas of modern technology. The programs prepare students with a broad scientific knowledge, an aptitude in a variety of mathematical techniques and the ability to synthesize. The exponential growth of technology and computing over the last decade has led to a growing demand for professionals in the field. Data has swept into every industry and business function and is now one of the most important factors of success, alongside labor and capital. This enormous growth of data has resulted in a high demand for data scientists world-wide. Career options include data scientist, data engineer, data analyst, statistician, data manager, data architect, business analyst.  

Learning Outcomes

A graduate with a M.S. in Computing & Data Science will have the ability to

  • Develop relevant programming abilities.
  • Demonstrate proficiency with statistical analysis of data.
  • Develop the ability to build and assess data-based models.
  • Execute statistical analyses with professional statistical software.
  • Demonstrate skill in data management.
  • Apply data science concepts and methods to solve problems in real-world contexts and will communicate these solutions effectively

Admission Requirements

  •  BS (SE/CS/IT/CE/EE/DS) 4 years degree program, or Computer Science conversion course two years degree program referred to as MCS or M.Sc. (Computer Science)
  • Candidates possessing four-year degrees in Mathematics, Statistics, Science & Engineering, are also eligible for entrance to this program, but may be required to take additional undergraduate courses.
  • Minimum 60% marks in previous degree in case of annual system or 2.5/4.0 CGPA in case of semester system with no more than one second division throughout the academic career.
  • No third division in entire academic career.
  •  Pass the following:

i. HEC(HAT)/ GAT-NTS (General) / UMT Graduate Admission Test(at least 50%).
ii. Admission Interview by UMT Graduate Admission Committee

Deficiency Courses:

Programming Fundamentals (Core Programming Course)

Data Structures & Algorithms OR Design & Analysis of Algorithms

Database Systems

Minimum Degree Completion Requirements

Program Duration = 2 years

Total Credit Hours = (8 Courses + Thesis)

Core Courses                                      4

Specialization Core                             2

Elective Courses                                 2

Core courses credit hours                    4 * 3 = 12

Specialization Core                              2 * 3 = 6

Electives courses credit hours              2 * 3 = 6

Thesis credit hours                               6

Total Credit Hours =                           30

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