Unique MS Data Science program offered at ITU

Due to the advancement of technology for data generation and data collection, zettabytes of data are being generated daily in many organizations. With the exponential increase in the volume of data, it becomes essential to discover hidden useful patterns from these large volumes. Data Science refers to the extraction of knowledge from large amounts of data. It is a process that uncovers important insights from huge amounts of raw data. More precisely we define data science as the use of sophisticated data analysis tools to discover previously unknown, valid patterns and relationships in large data sets.

The MS Data Science program at ITU will provide a comprehensive introduction to data science procedures; build theoretical and conceptual foundations of key data science tasks such as classification, association rule mining and clustering; discuss analysis and implementation of algorithms; and introduce emerging state-of-the-art research areas such as recommender systems, privacy preserving data mining, big data and business analytics. Emphasis will be placed on the design and application of efficient and scalable algorithms. The students will get hands on experience through the implementation of algorithms and use of software in assignments and the course project.

Why MS Data Science at ITU?

  • Prestigious Research Groups:
    • At the Information Technology University (ITU), several esteemed research labs are at the forefront of innovation, offering students unparalleled opportunities to engage in cutting-edge projects. The Data Science Lab, applies modern data mining and decision support systems to address challenges in government and corporate sectors, collaborating with international institutions. The Intelligent Machines Lab (IML) explores robotics, artificial intelligence, and human-computer interaction, aiming to solve real-world problems through technological advancements. The Center of Artificial Intelligence & Computational Science (CACTuS) focuses on machine learning, signal processing, and computer vision to develop efficient algorithms and industrial solutions. The Computer Vision Research Lab (CVRL) specializes in advanced computer vision techniques, pushing the boundaries of visual data interpretation. The Blockchain Security Lab delves into the intricacies of distributed ledgers, emphasizing security, programmability, and the development of decentralized applications. The Center for Intelligent & Personalized Adaptive Learning (CIPAL) focuses on building adaptive learning systems to enhance education through AI. The Virtual Reality Lab conducts cutting-edge research focused on developing immersive simulations for education, healthcare, and human-computer interaction. Lastly, the IHSAN Lab integrates technology with societal needs, focusing on human-centric computing solutions. Engaging with these labs not only enhances academic growth but also positions students at the nexus of research and practical application.
    • These research labs at ITU have published in leading international conferences and journals, developed state-of-the-art technologies in AI, blockchain, computer vision, data science, robotics, and human-computer interaction, and engaged in impactful collaborations with government bodies and global institutions. Their work spans from developing secure digital infrastructure and data-driven policy tools to creating real-time intelligent systems and socially-driven innovations, positioning ITU as a rising leader in applied research and interdisciplinary development.
  • Strong Publication Track Record: ITU’s different research groups have published more than 25 research papers in the highly prestigious data science venues in the last couple of years.
  • Bright Career Prospects: Six alumni of these research groups are proceeding with their doctoral studies in the top ranked universities of the world.
  • Real World Projects: Due to ITU’s close collaboration with PITB and Government of the Punjab, you would get an opportunity to work on real world, challenging, and socially relevant problems and datasets.

Employment Opportunities:

Data continues to be a key driver of innovation and decision-making across industries, making expertise in data science and analytics one of the most sought-after skill sets in 2025. The field has witnessed sustained growth in job opportunities, with Data Scientist consistently ranking among the top careers globally. According to Glassdoor, median base salaries for data scientists remain high, typically exceeding $125,000 in the US. On LinkedIn, thousands of new openings are posted weekly, reflecting growing demand in sectors like healthcare, finance, e-commerce, and government including roles such as Data Engineer, Data Analyst, Statistician, Machine Learning Engineer, Data Architect, and Business Intelligence Analyst. This evolving landscape underscores data science as not only a lucrative but also a resilient and future-ready career path.
Other career options include data scientist, data engineer, data analyst, statistician, data manager, data architect, business analyst.


Who can apply?

Applicants must fulfill the following criteria in order to be considered for admission into the MSDS program at ITU:

  • Completion of at least 16 years of education
  • An undergraduate degree in Computer Science, Data Science, Information Technology, Software Engineering, Electrical Engineering, Computer Engineering, Mechatronics Engineering, Electronics Engineering, Telecom Engineering, Mechanical Engineering, Civil Engineering, Mathematics, Statistics, Accounting, Economics, Management Sciences, Management and Technology, and MSc Mathematics or any other related field, from an HEC recognized university*
  • Scored 50% marks or above in matriculation, or equivalent examination.
  • Scored 50% marks or above in intermediate, or equivalent examination.
  • Scored at least 50% in the annual system, or CGPA of at least 2.0, in the terminal degree (Percentage will only be considered if CGPA is not mentioned on the transcript)
  • Scored at least 50% in the ITU Graduate Admissions Test
  • Those candidates who do not possess a strong CS background will be required to complete mandatory pre-required CS courses to compensate for their deficiency. The actual number of these courses will be decided at the time of admission

Details*

Required concepts and skills for MS Data Science/ MS Computer Science include: data structures, calculus, linear algebra and programming ability

General Notes

Note: Per HEC rules, candidates who have completed 12 years of education and obtained degrees other than Matriculation (SSC) or Intermediate (HSSC) may be required to obtain an equivalence certificate from the Inter Board Committee of Chairman (IBCC), Islamabad.

Applicants to the MS programs have to take the ITU Graduate Admission Test. A minimum score of 50% is required.
The ITU Graduate Admission Test will be held at the ITU campus in Arfa Software Technology Park in Lahore.
For information about dates please click here here.

Entry Test Pattern
Entry Sample Test

There will be no interview for MS Data Science degree program.

New Intake 2025

Semesters Tuition Fee University Dues Semester Wise Total Fee
First Semester 93,000 45,000 138,000
Second Semester 93,000 38,250 131,250
Third Semester 65,000 40,000 105,000
Fourth Semester 65,000 40,000 105,000
Total Degree Fee 316,000 163,250 479,250
  • A lump sum tuition fee will be charged for the semester as per the total required credit hours according to the approved roadmap/program structure of the respective degree program.
  • The fee for a summer semester, course repeat/improvement will be charged Rs.10,400/per credit hour.

Total Annual Cost Per Student (Approx.)

Cost Per Student (2024-2025) in PKR

Total Annual Cost Per Student (Approx) 721639
Subsidy from Provincial Government 66824
Subsidy from Federal Government 85514
Subsidy from ITU Endowment & investment incomes 334301
Student’s Contribution 235000
  • Total Annual Cost Per Student (Approx.)

For MS Batch 2024

Semesters Tuition Fee Other Dues Sem. Wise
Total Fee
Fall-2025 62,000 38,250 100,250
Spring-2026 62,000 38,250 100,250
124,000 76,000 200,500
  • A lump sum tuition fee will be charged for the semester as per the total required credit hours according to the approved roadmap/program structure of the respective degree
  • The fee for a course repeat/improvement will be charged For MS Programs: Rs.10,400/per credit hour.

Fee for International Students

Particular Fee for the International Students
Admission Fee 50$
University Dues (Per Semester) 200$
  • A 5% annual increment has been implemented on all dues.
  • Revised approved fee structure will be implemented from Fall-2025 session.

Degree Structure

The MS Data Science degree at ITU will develop real-world problem-solving skills using data science, which will differ from typical classroom problems. At ITU, we believe in the solution of problems with high social impact. The curriculum will also take into consideration the needs of the industry including stakeholders in business, social media, education, health, and entertainment. The MS program will prepare students to actively contribute to various fields, related to data science, such as computer vision, big data analytics, scientometrics, artificial intelligence, high-performance computing, and computer security.

Recommended Courses:

The following core courses are much recommended to be completed before entering the MS (DS) program.

  • Programming Fundamentals (Core Programming Course)/OOP
  • Data Structures & Algorithms OR Design & Analysis of Algorithms
  • Database Systems
  • Linear Algebra/Calculus/Statistics
MS DATA SCIENCE
Semester I
Sr. # Course Title Lecture Lab Credit Hours
1. Tools and Techniques for Data Science (core) 2 1 3
2. Statistical and Mathematical Methods for Data Analysis (core) 3 0 3
3. Machine Learning (core) 3 0 3
Total 8 1 9
Semester II
Sr. # Course Title Lecture Lab Credit Hours
4. Elective I 3 0 3
5. Big Data Analytics 3 0 3
6. Deep learning 3 3
7. Research Methodology 1 0 1
Total 10 0 10
First-Year Credit Hours 18 1 19
Semester III
Sr. # Course Title Lecture Lab Credit Hours
8. Elective II 3 0 3
9. Thesis I 3 0 3
Total 6 0 6
Semester IV
Sr. # Course Title Lecture Lab Credit Hours
10. Elective III 3 0 3
11. Thesis II 3 0 3
Total 6 0 6
Second-Year Credit Hours 12 0 12
Total Degree Credit Hours 30 1 31
Core Course
HEC-Recommended Specialization Courses
Elective Course
Research Thesis

The tentative list of graduate electives to be offered during the degree program is provided below.

Graduate Electives
Computer Vision
Blockchain
Deep Learning
Theory and Application of Virtual Reality
Spatial Data Science
Natural Language Processing
Theory of Automata- II
Medical Image Computing
Advanced Algorithms Analysis
Machine Learning
Cyber-Physical Systems
Introduction to Speech Processing
LLM and Generative Models
Remote Sensing: Data & Methods
ML and DL Ops
Cyber Security

*Please note that the list of electives is subject to change.

Probation Policy

      1. First-year students are required to maintain a minimum 1.50 CGPA; and from Second year onwards 2.00 CGPA to continue their studies at ITU and as a result of failing to achieve so, their admission will be revoked.
      2. For 2nd year and onwards, graduate students who earn a CGPA less than 2.50 shall be placed on Academic probation. The students on probation shall receive their results with a warning. After two warnings, if a student fails to improve his/her CGPA to 2.50 or above, and receives an academic probation for the third time, his/her name shall be removed from the University rolls.

Note: All students on 2nd probation will be allowed to enroll only for repeat courses in the next semester.

Level & Year Regular

(CGPA)

Probation

(CGPA)

Revoke

(CGPA)

Graduate

1st Year

2.50 & above 1.50-2.49 Less than 1.50
Graduate

2nd Year and Above

2.50 & above 1.50-2.49 Less than 1.50

Minimum Degree Requirement

Each department in the University shall certify its students to the Examinations Department for the award of degrees. The minimum requirement for the award of an undergraduate degree shall be a CGPA of 2.00 (on 4.00 scale).

Time Limit for the Completion of Degree

Time limit for the completion of the 4 years’ Undergraduate degree and Graduate/M.Phil. shall ordinarily be four years and two years respectively from the beginning of the first course counted towards the degree. However, a 4 years’ degree program can be extended up to 6 years and a 2 years’ degree program can be extended up to 4 years.

Credit Hour Requirements for Thesis

For the Graduate Thesis, a minimum of 16 credit hours must be completed.