M.Tech. in DSA

M.Tech. in DSA

M.Tech. in Data Science and Analytics

This is a two year post-graduate engineering programme supported by multidisciplinary faculty. Data is the new “oil”. Read more about this important field here.

This is a unique program for those who are interested in shaping and creating a future world where AI and Machine Learning, Natural Language processing, and business intelligence are providing opportunities and competitive advantages. It will empower the students with Data Science skills and competencies. The students will acquire the following skills: Research Design, Data Cleansing, Data Engineering, Data Mining and Exploring, Data Visualization, Information Analytics, Ethics and Privacy, Statistical Analysis, Machine Learning, Communicating Results, and many others.

mteh_xcse
The program is designed to educate data science leaders and help them earn a professional degree. The program features a multidisciplinary curriculum in computer science, statistics, management, and law.

Eligibility

BTech/BE, or MCA/MSc in CS/IT/CE/MATH/STAT streams, or MBA (or equiv.), with at least 55% aggregate marks or equivalent CGPA. (B.Sc. degree with an exceptional record and/or work experience can be considered). Candidates will be shortlisted based on academic credentials and Statement of Purpose (SoP). Shortlisted candidates will be invited for Personal Interview leading to the final unified selection. Candidates with a sound background in Mathematics and/or Statistics with at least basic coding knowledge are preferred

You may contact the Dean’s office for the program related questions (deanxcse_office@xub.edu.in or by phone). 

All admission-related queries may be directed to: admission@xub.edu.in
Phone: 0674 – 2377 806

 

Course Duration and Structure

The Curriculum is a blend of machine learning and programming and business-oriented subjects. The program includes an internship and a capstone project to foster interaction with the data science community and offers opportunities for applying data science knowledge.

Opportunities for various workshops such as SAS, Linux, Hadoop, Python, R will be available. 

Syllabus

The course has 4 semesters spread over 2 years. Core courses and electives offered are as follows.

Year One

Semester I

Semester II

Linear Algebra for Machine Learning
Big Data Management and Platforms
Introduction to Probability and Statistics
Text Analytics
Data Structure and Data Management for DS
Machine Learning and Predictive Analytics
Programming for Data Scientists
Elective-I
Data Mining and Exploration
Elective-II

Year Two

Semester III

Semester IV

Deep Learning
Elective-IV/Seminar
Causal Inference in Statistics
Thesis
Natural Language Processing
Elective-III
Capstone Project

Electives

The above list of electives is open and may be offered if sufficient demand exists.