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.
Admission Enquiry
Please fill the below fields for fee details, programme information, and application instructions
A bright future for Data Science professionals
Profile of M.Tech. Data Science and Engineering participants
Major Organisations where Participants work
Organisations where participants are employed at the time of joining the programme
Student Speak
- Programme Highlights
- Programme Curriculum
- Mode of Learning
- Eligibility
- Fee Structure
- How to Apply
- Mode of Examination
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
Semester-wise Pattern
Students need to take at least 12 courses towards coursework and complete one Dissertation. The coursework requirement for the programme would consist of a set of core courses and electives. Core courses are compulsory for all students, while electives can be chosen based on individual learning preferences.
First Semester
- Mathematical foundations for Data Science
- Introduction to Data Science
- Computer Organization and System Software
- Data Structures and Algorithm Design
Second Semester
- Introduction to Statistical Methods
- Elective 1
- Elective 2
- Elective 3
Third Semester
- Big Data Systems
- Elective 4
- Elective 5
- Elective 6
Fourth Semester
- Dissertation
Electives
- 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.
Mode of Learning
Mode of Learning
The Mode of Learning used in this programme is called - Work Integrated Learning. Internationally, Work Integrated Learning (WIL) is defined as "An educational approach involving three parties - the student, educational institution, and employer organization(s) - consisting of authentic work-focused experiences as an intentional component of the curriculum. Students learn through active engagement in purposeful work tasks, which enable the integration of theory with meaningful practice that is relevant to the students' discipline of study and/or professional development*.
An education model can be considered as WIL if and only if:
- The programs are designed and developed by the institute in collaboration with industry.
- Work-focused experiences form an active part of the curriculum.
- The program structure, pedagogy and assessment enable integration of theory-with relevant practice.
The innovative Work Integrated Learning Programs (WILP) of BITS Pilani are quite aligned with the above definition and requirements. The programs are designed in collaboration with its industry partners, subject matter experts from industry and academia that enable the students to remain relevant in their chosen profession, grow in their career and retain the habit of lifelong learning. The continued availability of workplace related experiences along with the weekly instruction sessions promote integration of theory with practice. An active participation of the organization mentor in the learning process of the student plays a key role. Case studies, simulation exercises, labs and projects further strengthen this integration.
The WILP of BITS Pilani is comparable to its campus-based programs in terms of structure, rigor, instruction, labs, assessment, faculty profile and learning support. The pervasive adoption of technology in all its academic processes makes the same high-quality education of BITS Pilani available to the aspirants at scale with the required flexibility.
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
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.
Eligibility
- 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.
Fee Structure
For fee details, programme information and application instructions, please click here to download the Programme Brochure.
How to Apply
For application instructions, programme information and fee structure, please click here to download the Programme Brochure
Mode of Examination
Mode Of Examination
Mode of Examinations applicable for students admitted in Batch starting in Oct/Nov 2024:
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.
For Indian Students:
Students can take their examination at any of our 33 designated examination centres in India at the following locations:
- South Zone: Bangalore - North, Bangalore - Central, Bangalore - South, Bangalore - East, Chennai - North, Chennai - Central, Chennai - South, Hyderabad, Secunderabad, Vijayawada, Visakhapatnam, Kochi, Thiruvananthapuram and Coimbatore.
- North Zone: Delhi, Gurugram, Noida, Jaipur, Chandigarh, Lucknow and Pilani.
- West Zone: Mumbai, Navi-Mumbai, Pune, Pune - Pimpri Chinchwad, Goa, Ahmedabad, Indore and Nagpur.
- East Zone: Kolkata, Bhubaneswar, Guwahati and Jamshedpur.
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.