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M.Sc. (Data Science)

Award Duration Study Mode
M.Sc. Data Science 2 Years (4 semesters) Full Time (on campus)
Intake Selection Process Program Starts
60 seats Entrance Test Yearly in July

Program OverviewThe M.Sc. in Data Science at DA-IICT brings together computational and statistical skills for effective data-driven problem-solving. This full-time program equips students with the analytical tools to design advanced technical solutions, emphasizing modern computational methods and rigorous statistical thinking.

Designed for those seeking to begin or advance their careers in data science, this professional master’s program welcomes students from various disciplinary backgrounds. Core courses provide a fundamental understanding of data science, covering key areas such as machine learning, data analysis, and data engineering while addressing data science's ethical and legal implications.

Our industry-relevant curriculum ensures students gain the skills to extract valuable insights from big data. Throughout the program, students will develop expertise in statistical modeling, data engineering, machine learning, data visualization, software engineering, research design, data ethics, and user experience. This comprehensive training meets the growing demands of industry, non-profits, government agencies, and other organizations.

To apply for the M.Sc. in Data Science program at DA-IICT, candidates must meet the following criteria:

Educational Qualifications

The candidate must possess one of the following qualifications.

  • Bachelor’s Degree in Science:
    • From a recognized university with a minimum aggregate of 60% or its equivalent.
    • Accepted disciplines: Statistics, Mathematics, Physics, Computer Science, Economics, Econometrics, Operational Research.
  • Bachelor’s Degree in Engineering or Technology:
    • From a recognized university with a minimum aggregate of 60% or its equivalent.
    • Accepted disciplines: Computer Science, Information Technology, Electronics, Electronics and Communication, Electrical Engineering.
  • Other Degrees:
    • Candidates holding BCA, B.Sc. (IT), B.Sc. (AI/ML), and B.Sc. (Data Science) degrees with a minimum aggregate of 60% or its equivalent.

Additional Requirements

  • Must have passed the 12th standard with Mathematics as a main subject.
  • Candidates appearing in their final degree examination and expecting to complete it by July 2024 may also apply. However, their final admission will be subject to obtaining a minimum aggregate of 60% marks or its equivalent. All admitted candidates must submit their degree certificates or proof of completion by 30 October 2024. Failure to do so may result in cancellation of their admission.

Notes

  • The decision of the concerned authorities of DA-IICT regarding the eligibility of any candidate shall be final.
  • There is no age limit applicable to this program.

We welcome diverse and qualified applicants who are eager to advance their careers in data science.

Industry-Relevant Curriculum

Data science is a fast-evolving field, and our curriculum is designed to equip students with the skills needed to meet the advancing needs of tomorrow. Master the essentials of Data Science through our diverse curriculum, covering all six pillars of data science: Mathematics, Statistics, Programming, Data Engineering, Machine Learning, and Ethics & Communication.

Program Breakdown

The M.Sc. Data Science is a 76-credit program, comprising:

  • Core Courses:
    • 2 Core Mathematics courses (7 credits)
    • 2 Core Statistics courses (8 credits)
    • 1 Core Programming course (4 credits)
    • 2 Core Data Engineering courses (8 credits)
    • 3 Core Machine Learning courses (12 credits)
    • 1 Core Ethics course (3 credits)
  • Elective Courses:
    • 8 credits, including courses from domain-specific applications.
  • Value-Added Courses:
    • 4 credits, taught by industry experts.

Project and Internship Opportunities

All students undertake a data science minor project (6 credits) under the guidance of a professor at DA-IICT. This project starts in the summer and concludes by the end of the third semester, focusing on a practical data science research question, either individually or as a team of two to three students.

For those seeking hands-on experience in a science and technology workplace or with research, the program offers a 6-month internship or the option to complete a major (research) project.

This comprehensive curriculum ensures that graduates are well-prepared to tackle the challenges and opportunities in the field of data science.

Semester I (Autumn I): Foundation Courses
Serial No. Course Name Credits (L-T-P)
1 Mathematical Foundations for Data Science 4 Credits (3-1-0)
2 Statistical Methods 4 Credits (3-0-2)
3 Data Structures and Algorithms in Python 4 Credits (3-0-2)
4 Introduction to Data Management 4 Credits (3-0-2)
5 Fundamentals of Machine Learning 4 Credits (3-0-2)
Total Semester Credits 20 Credits (15-1-8)
Semester II (Winter I): Advanced Courses
Serial No. Course Name Credits (L-T-P)
1 Numerical Optimization 3 Credits (2-0-2)
2 Interactive Data Visualization 4 Credits (3-0-2)
3 Big Data Engineering 4 Credits (3-0-2)
4 Neural Networks & Deep Learning 4 Credits (3-0-2)
5 Technical Elective - 1 4 Credits (3-0-2)
Total Semester Credits 19 Credits (14-0-10)
Summer Semester: Fostering for Industry
Serial No. Value Added Courses (compulsory): Total 60 hrs. Credits (L-T-P)
1
  • LLM Operations
  • Data Science in Industry: Case Studies
  • Communication Skills for Data Professionals
4 Credits (1-0-6)
2 Minor Project* 2 Credits (0-0-4)
Total Semester Credits 6 Credits (1-0-10)
Semester III (Autumn II): Specialized Courses
Serial No. Course Name Credits (L-T-P)
1 Machine Learning Systems Engineering 4 Credits (3-0-2)
2 Data Science Ethics 3 Credits (3-0-0)
3 Technical Elective - 2 4 Credits (3-0-2)
4 Minor Project (Continued…) 4 Credits (0-0-8)
Total Semester Credits 15 Credits (9-0-12)
Semester IV (Winter II): Industrial Training/ Research
Serial No. Course Name Credits (L-T-P)
1 Industrial Training/ Major Project (Pass/ Fail) 16 Credits (0-0-32)
Total Semester Credits 16 Credits (0-0-32)

List of Electives

  • Mathematics
    • Operational Research
    • Numerical Methods for Data Science
  • Statistics
    • Advanced Statistical Tools for Data Science
    • Time Series Forecasting
    • Applied Forecasting Methods
  • Data Engineering
    • Knowledge Graphs and Analytics
  • Machine Learning
    • Neural Natural Language Processing
    • Computer Vision
    • Digital Image Processing
    • Deep Reinforcement Learning
    • Multimodal Machine Learning
    • Generative AI
    • Federated Learning
  • Domain Specific Applications
    • Information Retrieval
    • Recommendation Systems
    • Health Informatics
    • Bioinformatics
    • Econometrics
    • Information Systems Security
    • Speech Communication
    • Policy Analysis

Faculty Expertise

Gain access to faculty with global experience and doctorates from prestigious institutions such as the University of Toronto, Carnegie Mellon University, University of Chicago, IITs, and other top universities worldwide. Our professors collaborate with industry and government to address real-world issues and integrate their research into the classroom. Additionally, teaching is complemented by sessions conducted by industry experts, providing students with practical insights and knowledge.

Peer-Learning Clubs (PLCs)

Engage with student-led learning communities that promote collaboration and a sense of belonging. These Peer-Learning Clubs (PLCs) enrich students’ academic journey by fostering a supportive and interactive learning environment.

Emphasis on Holistic Development

Experience a hands-on learning approach with regular assessments designed to ensure a well-rounded education. Our teaching methods include:

  • Surprise quizzes
  • Group projects
  • Case studies
  • 100-minute development challenges
  • Teach-the-teacher exercises

These activities are designed to enhance students' critical thinking, problem-solving, and communication skills, preparing them for the dynamic field of data science.

Outstanding Job Placement Success

Graduates of the M.Sc. in Data Science program at DA-IICT enjoy remarkable job placement success across a variety of roles, including: Data Scientist, Data Engineer, Data Analyst, Quantitative Analyst, Machine Learning Engineer, and Software Developer.

Our program boasts a noteworthy placement record within our postgraduate programs over the past years.

Employers in the Field

Our graduates are highly sought after by leading organizations across various sectors, including:

  • Consulting Firms: EY, KPMG, Futures First
  • Financial Services Companies: American Express, GiftStreet Capital
  • IT Companies: SAS R&D, Micron Semiconductor, Amazon Development Centre, Colgate Global, and many more.
  • Government Departments and Organizations: Indian Space Research Organisation (ISRO)
  • Universities and Public Research Institutions: IIT Gandhinagar, IIT Delhi, IIIT Hyderabad, CSIR, IPR, etc.

Technical and Professional Skills

Upon graduating from the program, students will possess a robust knowledge of modern statistical methodology and computing, equipping them for successful careers in data science.

Graduates will be able to demonstrate advanced critical analysis and independent inquiry skills, maintain intellectual integrity, and apply modern statistical methods and computing effectively. They will excel in writing, research, problem-solving, and communication, foster creative and critical thinking, and drive positive changes in their communities and workplaces.

Further Study

Upon completing the M.Sc. in Data Science, students may qualify to undertake a PhD (Doctor of Philosophy) in India or abroad, further enhancing their expertise and career prospects.

Fee

At the time of counselling an amount of Rs. 1,67,000 (Rs. 1,37,000/- towards Tuition Fee for the First Semester, Rs. 5,000 for Value Added Courses, and Rs. 25,000/- towards a Caution Deposit) - The registration fee is payable at the time of registration and hostel rent on allotment of the hostel room.

Tuition fee Rs. 1,37,000 per Semester
Value Added Courses Rs. 5,000 per Semester
Registration Fee Rs. 2,500 per Semester (including summer semester)
Caution Deposit Rs. 25,000 (Refundable at the end of the program)
Hostel Rent Rs. 27,500 per semester
Food On actuals. There are multiple food options available in the campus (The expense will be approximately Rs. 5,500 per month)

Subject to revision every Academic Year from 8 to 10%.

Merit & Merit-cum-Means Scholarships

The M.Sc Data Science Merit & Merit-cum-Means Scholarships are awarded to reward meritorious students of the M.Sc (Data Science) program throughout the program. The scholarship will be awarded semester-wise beginning from the second semester after the declaration of semester results. The scholarships will be awarded based on the SPI obtained each semester. The number of Scholarships will be limited to 7 (seven only) for a batch. The regulations on the award of Scholarships are as follows:

Eligibility and details of Scholarships

No. of Scholarships Type of Scholarship Eligibility conditions* Scholarship Band (Excluding SAS Certification fee)
Two (2) Merit Scholarships Top 2 SPI 8/10 and above scorers Full semester tuition fee
Two (2) Merit-cum-Means Scholarships SPI score: 7/10 and above + annual family income between Rs. 6.00 lakh and Rs. 8.00 lakh. 50% of the semester tuition fee
Three (3) Merit-cum-Means Scholarships SPI score: 7/10 and above + annual family income below Rs. 6.00 lakh. 70% of the semester tuition fee

* For 4th semester only CPI will be considered.

  • Other conditions
    • The student should have been registered for the semester subsequent to which the scholarship is awarded and should have paid the tuition and other fees in full by the given due date.
    • The student should PASS in all courses including course(s) audited, should not have any backlog, and/or disciplinary case(s) being initiated or recorded against her/him.
    • The Scholarship is awarded based on the performance of the student in a semester and the student has to meet the eligibility criteria in each semester to be eligible for the award of Scholarship.
    • In case a student withdraws from the program before completion of studies or her/his admission is terminated by the Institute or she/he is imposed any punishment/penalty due to indiscipline, the Institute has the right to recover the total scholarship amount paid to her/him.
    • The students applying for Merit-cum-Means should submit the Income Certificate from the designated statutory government authorities at the place of her/his residence and also the copies of the income tax returns of the parents. If the parents are not required to file returns as per IT Laws, a declaration from the parents to that effect should be submitted along with the application for Scholarship.
    • The student should not be recipient of any other Scholarship.
    • The selected student for award has to submit an undertaking stating that she/he will be bound by the regulations of the Scholarship Scheme.

UG/PG Cybage Khushboo Scholarships: Click here

The following links will be activated soon.

  • Academic Requirements
  • Detailed Syllabi of the Courses
  • Minor Project Policy
  • Minor Project Poster Template
  • Major Project Thesis Template
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