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BITS Work Integrated Learning Program - M.Tech Data Science & Engineering

     BITS Pilani offers work integrated learning program (WILP) on M.Tech Data Science and Engineering which is UGC approved.

The course is a four semester programme designed to help work professionals to build their skills required for data science engineering which enable them to become a Data Scientist. 

It is a 100% online course and lectures would be delivered by BITS Pilani faculty on weekends.

Those who are working in software industry as Software Engineer, Programmer, Data Analyst, Business Analyst can apply for the course.

Minimum eligibility criteria to apply for the course.

Those who are employed holding B.E/B.Tech/MCA/M.Sc or Equivalent with 60% marks and minimum one year relevant work experience. The candidates should have basic programming and engineering mathematics knowledge.

The following subjects shall be covered in the course.

Semester Subjects

  • Data Mining
  • Mathematical Fundamentals for Data Science
  • Data Structure and Algorithms Design
  • Computer Organisation and Systems Software
  • Introduction to Statistical Methods
  • Introduction to Data Science

Elective Subjects

  • Deep Learning
  • Natural Language Processing (NLP)
  • Artificial & Computational Intelligence
  • Real time Analytics
  • Data Visualisation & Interpretation
  • Algorithms & Mining Graphs
  • Optimization Methods for Analytics
  • Big Data Systems
  • Information Retrieval
  • Probabilistic Graphical Models
  • Data Warehousing
  • Systems for Data Analytics
  • Ethics for Data Science
  • Machine Learning
  • Distributed Data System
  • Stream Processing & Analytics
How to Apply


As the course is designed for working professionals, the employer consent form shall be submitted along with the application form. The candidates also must choose a mentor who would monitor and advice on the progress to complete the course successfully. The mentor can be immediate manager or a senior person who holds Bachelor degree with minimum of five years of relevant work experience of Master degree or equivalent.

Points to be noted for those who are willing to apply
  • The student strength for the course will be more. 
  • The students will be split into sections. 
  • The classes for sections will be conducted either on Saturday or Sunday. 
  • The each class will be for 2 hours and total 8 hours for four subjects from 9 AM to 7 PM on the assigned day.
  • There will be few webinars in week days evening also.
  • Approximately 16 units to be completed in each semester. Each unit corresponds to about 32 hours of study, which means at least 4 to 5 hours to be spent every day.
  • The evaluation process comprise of Assignments, Quizzes, Mid Semester and Comprehensive Exams.
  • As the course is for Master degree, self learning is expected from students.

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