Master of Science in Data Science (MS Data Science)

Data analytics and big data are now considered as strategic decision making in multi-disciplinary areas like finance, health, business, and engineering etc. In modern era, data scientists are becoming famous for applying advanced statistical and modeling techniques to resolve many data-driven problems including business processes and platforms. The Master of Science in Data Science (MS (DS)) program has been designed to enhance the students to be part of a data science endeavor that begins with the identification of various disciplines. This program will ensure the state-of-the-art trends and techniques to the students that can be useful for processing data science problems. Hence, in future, this program will build the nation with skilled and active data scientist for national and international market.

Following objectives are primary motives of this graduate program.

• To enhance the advance knowledge for graduates to get the actionable results by applying statistical and modeling techniques for complex business decisions.
• Graduated students can be able to analyze a solid problem and reached up to computable solutions.
• Students can be able to expose against the state-of-the-art technologies that matches with designed 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.
• Students understand handling data specially for data security and business ethics.

Registration in “MS Thesis/Project” will be allowed to register after completing minimum of 6 credit hours i.e., core courses.

This program equips students with latest tools, technologies and methodologies to solve complex data related problems. This is all about making sense of raw and structured data to extract meaningful information. The program covers mathematical and statistical foundations, Data Science Tools, Big Data Analytics, Natural Language Processing, and Information Visualization. In this course, there will be different case studies belonging to different areas such as: Telecom, Health sector, scientific domain, social media, customers’ data etc. The successful candidates will be able to pursue jobs in the following areas:

• Software development focusing acquiring, processing and visualizing data.
• Researchers focusing in data centric research methodologies by either innovating or effective usage of data strategies.
• Cyber Security Data Analyst
• Social Media Data Analyst
• Healthcare Data Analyst
• Enterprise Data Analyst
• Financial Data Analyst.

• A degree of BS (CS) as per HEC curriculum.
• Students with 16 years of education 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.
• Degree in relevant subject of Science or Engineering, earned from a recognized university after 16 years of education AND
• At least 60% marks or CGPA of at least 2.0(on a scale of 4.0).
• GAT-General conducted by ETS/NTS or any other recognized testing body including university admission test with at least 50%. marks

• A minimum of 2.5 CGPA out of 4.00.
• Completion of 30 SCH.

• The minimum duration to complete this degree is 2 years and not more than 4 years or 8 semesters. The degree will be terminated after completion of maximum duration.

According to the current rules of HEC, a thesis would enable students to have their degree vetted equivalent to an M.Phil. degree.

The classes will be held on campus. This will be an evening program usually having classes from 6:00 pm to 9:00 pm.

The mode of instruction will be in English. Each course may be evaluated based on quizzes, assignment, mid-term, semester projects, viva, reports, and final terms exams.