Master of Science in Data Science (MS DS)

Introduction:

The MS Data Science program is a 2-year advanced degree designed to equip students with the knowledge and expertise required to develop innovative data-driven solutions for real-world challenges. This program provides a thorough understanding of analyzing complex datasets and transforming them into actionable insights using cutting-edge data science techniques. The curriculum emphasizes the integration of computing, statistics, and domain-specific areas such as machine learning, big data analytics, data visualization, and predictive modeling. Students will gain proficiency in data wrangling, advanced analytics, and decision-making, enabling them to address diverse problems in sectors such as healthcare, finance, governance, e-commerce, and more. At Mohammad Ali Jinnah University, the program focuses on a hands-on learning approach through case studies, research projects, and access to state-of-the-art data science labs.

Ethical implications of data usage are explored in depth, ensuring graduates are equipped to apply data science responsibly and effectively for societal benefit. Our interactive learning model incorporates lectures, workshops, and project-based learning, fostering a collaborative environment aligned with modern data-driven industries. This program prepares graduates for high-demand roles in data science, analytics, and research, empowering them to create transformative solutions for the future.

Program Objectives

Sr# Details 1 To provide students with strong substance of theoretical knowledge and research in computer science. 2 To provide students with competent skills of solving complex computational problems and expedite modern research in computer science. 3 To provide students with awareness and knowledge of Social, Ethical, and Professional values relevant to Computer Science Research.

Essential Requirements for the MS(DS) Degree:

The following are the fundamental requirements to get admission and complete an MS(DS) degree at Muhammad Ali Jinnah University, Karachi, Pakistan.

Category Details Eligibility

• A minimum of 16 years of education or equivalent in relevant subject
• Applicants with undergraduate degrees from non-relevant areas may be required to take some undergraduate courses to fulfill pre-requisite deficiencies as determined by the Graduate Admission Committee. The deficiency Cr. Hrs. will not be counted towards the minimum Cr. Hrs. requirement for the award of the MS degree.
• Minimum 2.00/4.00 CGPA or 60% marks

Selection Criteria

• Admission Test / HEC Approved Test
• Interview

Program Duration

• 1.5 to 2 years (3-4 regular semesters – Fall & Spring)

Maximum Duration

• 4 years

Degree Requirements

• 24 Cr. Hrs. Course Work and 06 Cr. Hrs. Thesis / 27 Cr. Hrs. Course Work and 03 Cr. Hrs. Research Project
• Minimum CGPA of 2.5 out of 4.0

Total Credit Hours

• 30

Definition of Credit Hour:

• 1 contact hour of theory or 3 contact hours of lab.

Deficiencies

• Max 9 credit hours (for students with non-relevant backgrounds like Information Technology, Software Engineering, Computer Engineering, Electrical/Electronic Engineering, Statistics, or Mathematics)

Deficiency Courses

• Programming Fundamentals
• Data Structures & Algorithms OR Design & Analysis of Algorithms
• Database Systems

Generic Structure for MS(DS) Discipline:

Areas Credit Hours Courses Core Courses 12 4 Elective Courses 12 4 Thesis 6 Totals 30 8

OR

Areas Credit Hours Courses Core Courses 12 4 Elective Courses 15 5 Research Project 3 Totals 30 9

Elective Courses:

The list of possible elective courses is provided below.

Sr# Course Title Sr# Course Title 1 Deep Learning 15 Computational Biology 2 Agile Software Project Management 16 Software Test Automation 3 Cyber Security 17 Digital Forensics 4 Cloud Computing 18 Topics in Network Security 5 Internet of Things 19 Enterprise Information Security 6 Digital Image Processing 20 Information Security Management 7 Natural Language Processing 21 Distributed Systems 8 Computer Vision 22 Communication and Information Policy 9 Business Process Engineering 23 Data Mining 10 Software Risk Management 24 Machine Learning 11 Big Data Analytics 25 Information Retrieval Techniques 12 Generative AI 26 Natural Language Processing 13 Software Agents 27 Semantic Web 14 Artificial General Intelligence 28 Bioinformatics