M.Tech. Data Science and Engineering

Admissions open for Oct’25 Batch

Specialization in

Deep LearningNLPAudio and Vision

M.Tech. Data Science and Engineering

According to LinkedIn's Emerging Jobs report, Data Science has emerged as the fastest-growing job globally, with a remarkable growth rate of over 650% since 2012. Moreover, the Data Science market is predicted to follow an upward trajectory, increasing from USD 37.9 billion in 2019 to a projected value of USD 230.80 billion by 2026.

Prepare for a career in Data Science with India’s most comprehensive and world-class M.Tech. Data Science & Engineering Programme without taking a career break. This four-semester programme by BITS Pilani WILP enables Software and IT professionals to build stellar skill set required to advance their career as a Data Analyst, Data Engineer, Data Architect, and Data Scientist, etc.

Option to pay fees using easy EMI with 0% interest and 0 down payment.

Study without

Career Break

EMI Option With

0% Interest & 0 down payment

Admissions Open

Oct’25 batch

Fees per semester

INR 75,100

M.Tech. Data Science & Engineering Video

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Programme Highlights

The M.Tech. Data science and engineering is a Work Integrated Learning Programme (WILP) spanning four semesters. BITS Pilani's Work Integrated Learning Programmes are approved by the University Grants Commission (UGC).
Attend live-lectures from anywhere over an online technology-enabled platform. These live lectures would be conducted by faculty mostly on weekends or after business hours enabling working professionals to pursue the programme along with their jobs.
Offers the most comprehensive Data Science Curriculum for working professionals.
The programme has an unmatched range & depth, and covers fundamentals to advanced skill & knowledge areas associated with the domain of Data Science.
Aimed at transitioning software & IT professionals into Data Science careers tracks closest to their interest/passion.
Curriculum maps knowledge and skill areas required to perform popular Data Science job roles such as Data Analyst, Data Engineer, Data Architect, and Data Scientist, etc.
The programme offers a set of core courses and elective courses, allowing students to specialize in Data Management for Machine Learning, Ethics for Data Science, Optimization Techniques for Analytics, Natural Language Processing, etc.
The programme makes use of Tools and Technologies. These include Apache Spark, Apache Storm for Big Data Systems/ Real time Processing; Tableau for data visualisation; Tensorflow for Deep Learning; Various Packages within Python for data processing, machine learning, data visualization etc.
The Dissertation (Project Work) in the final semester enables students to apply concepts and techniques learned during the programme.
The programme uses a Continuous Evaluation System that assesses the learners over convenient and regular intervals. Such a system provides timely and frequent feedback and helps busy working professionals stay on course with the programme.
The education delivery methodology is a blend of classroom and experiential learning. Experiential learning consists of lab exercises, assignments, case studies and work-integrated activities.
Students who successfully complete the programme will become members of an elite & global community of BITS Pilani Alumni
Option to submit fee using easy-EMI with 0% interest and 0 down payment .

Programme Curriculum

Students need to take at least 12 courses towards coursework, and complete one Project/ Dissertation. The coursework requirement for the programme would consist of a set of core courses and electives. Core courses are compulsory for all student, while electives can be chosen based on individual learning preferences.

Mathematical foundations for Data Science
Introduction to Data Science
Computer Organization and Software Systems
Data Structures and Algorithm Design

Introduction to Statistical Methods
Elective 1
Elective 2
Elective 3

Big Data Systems
Elective 4
Elective 5
Elective 6

Dissertation

Data Warehousing
Graphs – Algorithms and Mining
Deep Learning*
Probabilistic Graphical Models
Ethics for Data Science
Optimization Techniques for Analytics
Data Management for Machine Learning

Natural Language Processing
Design of Experiments for Data Science
Information Retrieval
Data Visualization and Interpretation
Stream Processing and Analytics
Artificial and Computational Intelligence
Machine Learning *
Applied Machine Learning

*Machine Learning course is a prerequisite for Deep Learning elective course.

Note: Choice of Electives is made available to enrolled students at the beginning of each semester. Students' choice will be taken as one of the factors while deciding on the Electives offered. However, Electives finally offered will be at the discretion of the Institute

For detailed programme curriculum, download the brochure.

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Mode of Learning

The Mode of Learning is based on a powerful educational approach called Work Integrated Learning. For detailed description of work integrated learning Click here

The benefits of the Work Integrated Learning Mode are as follows:

1) It enables Working Professionals to pursue the programme without any career break and along with their jobs.

2) The programme curriculum is designed for high relevance to sectors, industries and organisations the students are presently employed in.

3) Learning experience design also endeavours to integrate support and value addition by the Industry Mentors and employer organizations.

4) Enables working professionals to attend live-lectures from anywhere over an online technology-enabled platform. For the benefit of working professionals these live lectures are conducted by faculty mostly on weekends or after business hours.

5) Leverages the latest educational technologies to provide easy access to asynchronous learning materials, Learner support services and peer to peer collaboration etc.

6) Great emphasis on experiential learning by providing access to state of the art remote labs, virtual labs and cloud labs and simulations as applicable to individual courses.

EXPERIENTIAL LEARNING

The programme emphasises on Experiential Learning that allows learners to apply concepts learnt in the classroom in simulated, and real work situations. This is achieved through:

Simulation Tools, Platforms & Environments: Some or all of the following would be utilised across the programme.

Cloud based virtual lab which supports the following programming languages/tools/simulators:
- Networks: NS2, Net-SNMP and WireShark
- Data Analytics:
  - Languages: R, Python, Prolog and Lisp
  - Platforms: RStudio, Weka, Microsoft Power BI, TensorFlow and Anaconda Navigator
  - Libraries: Python Ecosystem – NumPy, SciPi, Pandas, scikit-learn, MatplotLib; Searborn, Keras, NLTK, pgmpy etc.
  - Embedded and IOT: Keil, CCS Studio, Tossim and Cheddar
  - Devops: Jenkins, GitHub, SonarQube, Selenium, Tomcat and Maven
  - Programming Environments: Java, Eclipse, Code::Blocks, Android Studio, Jupyter Notebooks and Spyder
  - Others: Multisim, CPU-OS Simulator, SQLite, MATLAB, , Gantt Project, Open Project and XAMPP
Remote Lab facility caters to the needs of resource intensive requirements of Big Data Analytics applications with the following platforms:
- Apache Hadoop
- Apache Storm
- Apache Spark
- Apache Kafka
- MongoDB
- CockroachDB
- MPI
Remote Lab facility caters to the needs of Embedded Systems and IoT. It supports the following:
- Hardware / Software tools: MultiCore STM32 microcontroller based development boards.
- Simulation tools: Tossim, Cheddar and Keil

CONTINUOUS ASSESSMENT

Continuous Assessment includes graded Assignments/ Quizzes, Mid-semester exam, and Comprehensive Exam.

CASE STUDIES AND ASSIGNMENTS

Carefully chosen real-world cases & assignments are both discussed and used as problem-solving exercises during the programme.

DISSERTATION/ PROJECT WORK

The fourth semester offers an opportunity for learners to apply their knowledge gained during the programme to a real-world like complex project. The learner is expected to demonstrate understanding of vital principles learnt across semesters and their ability to successfully apply these concepts.

Key Benefits of BITS Pilani WILP

1) Can pursue the programme without any career break and along with the job.

2) The programme curriculum is highly relevant to sectors, industries and organisations they work for

3) In addition to the institute, the learning experience of working professionals in the programme is also supported by the employer organisation and Industry Mentors.

4) Effective use of technology to deliver a range of learning interventions at the location of the working professional such as faculty contact sessions, asynchronous learning materials, remote, virtual and cloud labs, Learner support, peer to peer collaboration etc.

5) Contact sessions with faculty take place mostly over weekends or after business hours and are conducted over a technology platform that can be accessed from anywhere.

6) Mid semester and End semester examinations for every semester are conducted mostly at designated examination centres distributed across the country (for details refer to link mode of examinations)

7) Learners can access engaging learning material which includes recorded lectures from BITS Pilani faculty members, course handouts and recorded lab content where applicable.

EXPERIENTIAL LEARNING

The programme emphasises on Experiential Learning that allows learners to apply concepts learnt in classroom in simulated and real work situations. This is achieved through:

Tools & Technologies: Apache Spark, Apache Storm for Big Data Systems/ Real time Processing; Tableau for data visualisation; Tensorflow for Deep Learning and various Python libraries for data processing, machine learning, OpenCV for computer vision, NLTK for NLP etc..

CONTINUOUS ASSESSMENT

Continuous Assessment includes graded Assignments/ Quizzes, Mid-semester exam, and Comprehensive Exam.

CASE STUDIES AND ASSIGNMENTS

Carefully chosen real-world cases & assignments are both discussed and used as problem-solving exercises during the programme.

DISSERTATION/ PROJECT WORK

Mode Of Examination

Mode of Examinations applicable for students admitted in batch beginning in April 2025:

Semester 1, 2 and 3 have Mid-Semester Examinations and Comprehensive Examinations for each course. These examinations are mostly scheduled on Friday, Saturday or Sunday. Students need to appear in person for taking the examinations at the institution’s designated examination centres as per the examination schedule, Instructions, rules and guidelines announced before every examination.

Students can take their examination at any of our 27 designated examination centres in India at the following locations:

South Zone: Bangalore, Chennai, Hyderabad, Vijayawada, Visakhapatnam, Kochi, Thiruvananthapuram, Coimbatore

North Zone: Delhi NCR, Gurugram, Noida, Faridabad, Jaipur, Chandigarh, Lucknow, Udaipur, Pilani

West Zone: Mumbai, Pune, Ahilya Nagar, Goa, Ahmedabad, Indore, Nagpur,

East Zone: Kolkata, Guwahati, Bhubaneswar

For International Students:

In addition to the above locations, the institution also has a designated international examination centre, located in Dubai.
To facilitate the learning of international students, applying from any other location except India and Dubai, the mode of examinations will be online, which can be availed by meeting the requirements of the institute.
To know more about the requirements for online examinations, Click here

Indian students, who are temporarily based out of India, can also avail of online examinations on request by meeting the above-mentioned requirements of the institute.

Eligibility Criteria

Employed professionals holding B.E. / B.Tech. with at least 60% aggregate marks and minimum one-year relevant work experience after the completion of the degree are eligible to apply.
Employed professionals holding MCA / M.Sc. or equivalent with at least 60% aggregate marks with university level mathematics / statistics as mandatory subjects and minimum one-year relevant work experience after the completion of the degree are also eligible to apply.
Applicants should possess basic programming knowledge and adequate background in Mathematics.

How to Apply

Points to Note

a) Make photocopies of the documents mentioned in this Checklist.
b) Applicants are required to self-attest all academic mark sheets and certificates.
c) On page no. 3 a section called the Employer Consent Form. This form needs to be autthorized by your organisation’s HR or any other authorised signatory of the company.
d) On page no. 4 is a section called the Mentor Consent Form. The Mentor Consent Form needs to be signed by the Mentor. Click here to know who could be a Mentor.

Batch Profile

UGC Approval

BITS Pilani is an Institution of Eminence under UGC (Institution of Eminence Deemed to be Universities) Regulations, 2017. The Work Integrated Learning Programmes (WILP) of BITS Pilani constitutes a unique set of educational offerings for working professionals. WILP are an extension of programmes offered at the BITS Pilani Campuses and are comparable to our regular programmes both in terms of unit/credit requirements as well as academic rigour. In addition, it capitalises and further builds on practical experience of students through high degree of integration, which results not only in upgradation of knowledge, but also in up skilling, and productivity increase. The programme may lead to award of degree, diploma, and certificate in science, technology/engineering, management, and humanities and social sciences. On the recommendation of the Empowered Expert Committee, UGC in its 548th Meeting held on 09.09.2020 has approved the continued offering of BITS Pilani’s Work Integrated Learning programmes.

Industry Talks

The programme features Industry Talks on some of the most exciting developments, and pressing issues faced by businesses in the technology space. Speakers include business leaders, R&D professionals, and academicians from leading technology firms and institutions.

Some of the recent and upcoming sessions include:

Title of Tech Talk	Date	Speaker(s) and Profile
The New Language of Cloud Value: FinOps and the Journey Beyond the Bill	April 2025	Kumar Yarlagadda currently serves as the Cloud Foundation Lead at Heineken Global, where he oversees cloud service governance across the organization.
Recent Advances in Unsupervised Learning & Text Mining & Deep Learning	April 2025	Prof. Sudarshan Deshmukh, AI Architect - Laya Healthcare, CEO DeepIntutionAI, Guest Faculty at BITS https://www.linkedin.com/in/sudarshan-deshmukh-0040a115/
Hardware Components of Robots - AIML Perspective	April 2025	Prof. Rajiv Rajan Gupta, Assistant Professor (Off Campus), Department of Mechanical Engineering, BITS Pilani https://www.linkedin.com/in/rajiv-ranjan-gupta-27980a165/?originalSubdomain=in
Big Graphs Mining	February 2025	The speaker was Mr. Bipin Sinha, he is working in the area of big graphs.
AI Frameworks for Engineering Applications.	February 2025	Mr. P V S MARUTHI RAO .Mr Maruthi Mathapati has 25+ years of diversified experience in development of infrastructure software and systems, leading engineering teams, managing start-ups, technology and business management and has mentored a few tech-startups.
Industry relevance of AI	December 2024	Philip Varughese: Global Head – Cyber Risk & Compliance, Applied Intelligence, Platforms & Engineering, at DXC
Role of Full Stack(From Edge to Edge)with AI/ML Frameworks	Nov 2024	Mr Maruthi Mathapati
Applied AI Blueprint	November 2024	Mr. Santosh GSK, Co-Founder, Volkano AI Founder GradCommerce Digital Content Creator - BITS https://www.linkedin.com/in/santoshgsk/?originalSubdomain=in
Building relations with stakeholders and its role in career growth	October 2024	Speaker was Mr Shailendra Mruthyunjayappa (https://www.linkedin.com/in/mruthyunjayappa/) who is the CEO of Fintellix, a leader in Financial Regulatory Tech space.
Dashboard Design Essentials	October 2024	Jishnu Sarkar, Lead of People and Organization Development at Goalkeep Advisors
Data Visualization: In All Its Forms and Facets	October 2024	Kuhu GuptaKuhu Gupta — Data Visualization Engineer \| Senior Member of Technical Staff at Illumio
Case Studies in Text Mining & Deep Learning	October 2024	Prof. Sudarshan Deshmukh, AI Architect - Laya Healthcare, CEO DeepIntutionAI, Guest Faculty at BITS https://www.linkedin.com/in/sudarshan-deshmukh-0040a115
Recent Advances in Generative AI	October 2024	Mr. Santosh GSK — Co-Founder, Volkano AI \| Founder, GradCommerce \| Digital Content Creator, BITS https://www.linkedin.com/in/santoshgsk/?originalSubdomain=in
MLOps - Existing and Future Trends	July 2024	Amit Kumar is Sr. Software Architect (AI/ML) @ Dazn, Ph.D scholar and Adjunct Faculty @ BITS-Pilani.
LLMs - what and how?	July 2024	Mahathi Bhagavatula is founder at Hey DTC where she scales your revenue without increasing your Ad Budget. She is also Co-Founder at Volkano AI.
Power BI for effectively visualizing data	July 2024	Dr. Madhusudhanan Baskaran, Chief Data & AI Strategist, Centre for Human Centric Artificial Intelligence - Initiative of IITM-Pravartak and IIT Madras · Freelancer
Visual Analytics and Applications in AI	June 2024	Shivam Agarwal, Scientific Researcher – Utrecht University

Fee Structure

The following fees schedule is applicable for candidates seeking new admission during the academic year 2024-2025.

Application Fees (one time) : INR 1,500
Admission Fees (one time) : INR 16,500
Semester Fees (per semester) : INR 75,100

The one-time Application Fee is to be paid at the time of submitting the Application Form through the Online Application Centre.

Admission Fee (one-time) and Semester Fee (for the First Semester) are to be paid together once admission is offered to the candidate. Thus, a candidate who has been offered admission will have to pay Rs. 91,600/-. You may choose to make the payment using Netbanking/ Debit Card/ Credit Card through the Online Application Centre.Fee payment by easy-EMIs with 0% interest. Click here to learn more.

Semester Fee for subsequent semesters will only be payable later, i.e. at the beginning of those respective semesters.

Any candidate who desires to discontinue from the programme after confirmation of admission & registration for the courses specified in the admit offer letter will forfeit the total amount of fees paid.

For the examination centre at Dubai, in addition to the semester fees, for each semester there will be an examination centre fees of 1000 UAE Dirhams or equivalent per semester out of which 500 UAE Dirhams is to be paid at the time of appearing in Mid-semester examinations at Dubai Centre for that semester and the remaining 500 UAE Dirhams is to be paid at the time of appearing in comprehensive examinations at Dubai centre for that semester.

All the above fees are non-refundable.

Important: For every course in the program institute will recommend textbooks, students would need to procure these textbooks on their own.

FAQs

Yes, UGC has approved the continued offering of M.Tech. Data Science & Engineering as a part of WILP on the recommendations of Empowered Expert Committee. Click here to learn more.

This programme is designed for working professionals. At the time of submitting the application, candidates must be employed in another organization. Professionals who are owners of a registered business are also eligible to apply. For detailed information, including academic background, work experience, etc. refer to the programme eligibility criteria.

Contact classes are conducted over a technology enabled platform. These classes can be attended via the internet using a computer from any location. These contact classes offer similar levels of interactivity as regular classrooms at the BITS Pilani campus. These are conducted usually over weekends or after business hours for a total of 7-8 hours per week. If you miss a lecture, you can also access the recorded lecture on the internet.

Upon successful completion of the programme, students will receive a degree certificate from BITS Pilani.

The Degree of Master of Technology in Software Systems

Each semester has a Mid-semester Exam and a Comprehensive Exam for each course , which are conducted over weekends. Students will need to appear in-person to take these exams at exams centers in the following locations:
India Centers:

Students can take their examination at any of our 27 designated examination centres in India at the following locations:

South Zone: Bangalore, Chennai, Hyderabad, Vijayawada, Visakhapatnam, Kochi, Thiruvananthapuram, Coimbatore

North Zone: Delhi NCR, Gurugram, Noida, Faridabad, Jaipur, Chandigarh, Lucknow, Udaipur, Pilani

West Zone: Mumbai, Pune, Ahilya Nagar, Goa, Ahmedabad, Indore, Nagpur,

East Zone: Kolkata, Guwahati, Bhubaneswar

International Centers: Dubai
In case students are unable to take an exam due to work-related commitments, there is also a provision of appearing for Make-up Exams.

The programme provides a high degree of interactivity between students and the faculty members and programme instructors. Q&A sessions during the contact classes (which you can attend from anywhere over a technology enabled platform) allow participants to pose questions to the faculty members, and seek guidance through voice and chat. Further interaction with faculty members and peers is enabled through the e-learning portal, by using discussion forums and message boards.

The programme features high usage of experiential learn components such as Simulations, Virtual Labs, and Remote Labs, in order to mimic the on-campus experience.

Participants will be given access to portals, that will allow them to access both cloud-based labs, as well as Campus-based physical labs. Using leading industry-recognised Software tools, Programming languages, and Simulation software, participants will be able to perform experiments and run simulations to advance their knowledge

Candidates applying to the programmes must choose a Mentor, who will monitor the academic progress of the candidate, and act as an advisor & coach for successful completion of the programme. Candidates should ideally choose the immediate supervisor or another senior person from the same organisation. In case a suitable mentor is not available in the same organisation, a candidate could approach a senior person in another organisation who has the required qualifications. For detailed information, please refer to the programme brochure.

The programme is designed for working professionals, and participants are not required to travel to a BITS campus. However, certain programme offer Campus Immersion Modules such as workshops or seminars, which are highly recommended but not mandatory.

M.Tech. in Data Science & Engineering is a post-graduate programme from BITS Pilani WILP that covers topics such as machine learning, data mining, big data technologies, data visualization, and statistical analysis.

Applicants applying for M.Tech. in Data Science & Engineering programme are required to meet the following criteria:

Working professional with B.E. / B.Tech. or equivalent degree with a minimum of 60% overall marks.
Along with minimum of one year of relevant work experience after your degree

Working professional with MCA / M.Sc. degree or an equivalent qualification with at least 60% overall marks
Studied Mathematics or Statistics at the university level

Graduates of M.Tech. in Data Science & Engineering programme are in high demand in today’s world, due to the increasing importance of data-driven decision-making abilities in industries, such as IT, Retail, Automotive, Manufacturing, Finance, Healthcare, e-commerce, and Telecommunications. Some of the job roles that graduates can explore include data scientist, data analyst, business analyst, machine learning engineer, and big data engineer.

To pursue M.Tech. in Data Science & Engineering programme, applicant should have a strong foundation in mathematics, statistics, and programming. Additionally, skills, such as data analysis, data visualization, machine learning, problem-solving, and critical thinking would be bonus.

The M.Tech. in Data Science & Engineering programme spans two years and is divided into four semesters.