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:
  • 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 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. Here are some pointers to show this high demand:

  • Data Scientist is rated the best job in America for 2017, with a median base salary of $110,00. (Source: Glassdoor).
  • There are approximately 215,000 open job positions in Data Science (Source:Indeed.com).
  • There are currently about 31,000 openings for Statistician positions in the US (LinkedIn), offering an average salary of $77,000 (Glassdoor).
  • In the field of Business intelligence, there are around 14,000 openings in the US (LinkedIn) at a $88,000 base salary.

Other career options include data scientist, data engineer, data analyst, statistician, data manager, data architect, business analyst.

  • Eligibility Criteria
  • Admission Test
  • Interview/Assessment
  • Fee Structure
  • Program Structure
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, Electrical Engineering, or any other related field, from an HEC recognized university*
  • Scored at least 60% in the annual system, or CGPA of at least 2.5, in the terminal degree
  • Scored at least 60% in the ITU Graduate Admissions Test


Required concepts and skills include: data structures, databases, 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 60% is required.
The ITU Graduate Admission Test will be held at the ITU campus in Arfa Software Technology Park in Lahore.
SOPs for Covid-19, as prescribed by the government, will be strictly followed.
For information about dates please click here here.

Entry Test Sample

Entry Test Pattern

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

Program Duration 4 semesters (2 years)
Tuition Fee per Credit Hour Rs. 6,500
Total No. of Credit Hours 31
University Charges Per Semester Rs. 24,000

Note: If the fee exceeds Rs. 200,000 per annum, 5% Income Tax will be added u/s 236I of the Income Tax Ordinance, 2001.


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
Semester I
S.No. Title of Course Credit Hours
1. Tools and Techniques for Data Science 2+1 (lab)
2. Statistical and Mathematical Methods for Data Analysis 3
3. Information Retrieval and Text Mining 3
4. Research Methodology 1
Semester II
S.No. Title of Course Credit Hours
1. Machine Learning 3
2. Big Data Analytics 3
3. Deep learning 3
Semester III
S.No. Title of Course Credit Hours
1. Elective Course 3
2. Thesis I 3
Semester IV
S.No. Title of Course Credit Hours
1. Elective Course 3
1. Thesis II 3
Total Degree Credit Hours 31
Some Important Elective Courses Offered:
  • Natural Language Processing
  • Computer Vision
  • Speech Processing
  • Blockchain
  • Pattern Recognition
  • Approximation Algorithms
  • Internet of Things (IoT)