Duration of Program 2 Years (4 Semesters)


Seats 10 only

In this specialisation, students learn about essential concepts such as data structures, algorithms, OOPS concepts using Java, databases, software engineering and design processes. Students will also obtain an in-depth knowledge of machine learning and artificial intelligence by implementing relevant real-world problems in a wide variety of application domains such as robotics, computer vision, natural language processing, etc. Students will be experienced in machine learning pipeline, data, models, algorithms, and empirics.

Co-Delivered Courses by Partner Industries


The foundation of higher learning at UPES since its inception has been to explore and promote areas of learning that are innovative and future focused. This has led to constant evolution in facilitating creative and collaborative learning engagements for students through realignment of curriculum and exploration of virtual tools, and open-source courseware; thereby creating borderless learning and access to limitless information.

The new curriculum framework at UPES, ABLE (Academic Blueprint for Learning Excellence) is holistic in its overall structure and yet focuses on the individual need of the student to discover, experience, explore and challenge. The learning is segmented into core subject studies, core specialism studies, minors/exploratory subjects, and signature and life skills learning. The latter three are offered by the newly-instituted School for Life.

SFL (School for Life) is an intrinsic part of the composite UPES student experience and facilitates learning and education that is a balance between what students want, and what is needed of them as future global citizens and leaders of tomorrow. With courses designed to equip students with lifelong learning skills, a focus on a wide range of contemporary issues, and a mandatory social and professional internship experience that is unique, UPES believes in igniting to inspire the best version within an individual to better the world.


Screening of Application and Interview
GATE Scholarship:

  • Scholarship @ Rs. 12,400/- per month for Students having 70 percentile and above in GATE.
  • Students admitted to M. Tech program in the academic session 2020-21 with valid GATE score 70 percentile and above will be considered for scholarship @ Rs. 12,400/- per month during their period of registration with the University.


All Students will also be eligible to avail a grant up to a sum of Rs. 50,000/- towards outcome-based research as per rules & regulations framed for the purpose by the University.

To become eligible for the continuance scholarship in subsequent semesters, the students are required to have 

  • earned minimum SGPA / CGPA of 8.0 in each semester
  • passed every semester examination in the first attempt besides maintaining regular attendance, discipline, exemplary behavior and compliance with all other norms as prescribed by the University from time to time

Disclaimer: Only one category of scholarship can be availed by student, Multiple scholarship to one candidate will not be granted 



Subject Code Subject Credits
CSEG 7001 Algorithm Design and Analysis 3
CSEG 7002 Advance Database Management Systems 3
CSEG 7003 Statistical Modelling for Computer Sciences 3
Elective I (Choose Any One) 3
CSCS 7001P Data Security  
CSAI 7003P Artificial Intelligence & Expert Systems  
CSDA 7001P Data Mining & Business Intelligence  
CSIP 7001P Computer Graphics  
Elective II (Choose Any One) 3
CSCS 7002P Cyber Security and Ethics  
CSAI 7004P Fuzzy Logic and Application  
CSDA 7002P Predictive Modelling  
CSIP 7002P GPU Architecture and Programming  
CSEG 7101 Algorithm Design and Analysis Lab 1
CSEG 7102 Advance Database Management Systems Lab 1
CSEG 7103 Statistical Modelling for Computer Sciences Lab 1
  Total 18





Subject Code Subject Credits
CSEG 7004 Data Communication and Computer Networks 3
CSEG 7005 Modelling & Simulation of Digital Systems 3
Elective III (Choose Any One) 3
CSCS 7003P Forensic Computing  
CSAI 7005P Artificial Neural Network & Its Applications  
CSDA 7003P Big Data Analytics  
CSIP 7003P Computer Vision  
Elective IV (Choose Any One) 3
CSCS 7004P Security of e-Systems and Networks  
CSAI 7006P Natural Language Processing  
CSDA 7004P Decision Management Systems  
CSIP 7004P Digital Image Processing  
Elective V (Choose Any One) 3
CSCS 7005P Cryptography and Cryptanalysis  
CSAI 7007P Machine Learning  
CSDA 7005P NoSQL Database Management  
CSIP 7005P Document Image Processing and Compression  
CSEG 7105 Modelling & Simulation of Digital Systems Lab 1
CSEG 7104 Data Communication and Computer Networks Lab 1
  Total 17





Subject Code Subject Credits
SIIB 8102 Summer Internship 7
PROJ 8105 Project I 12
  Total 19





Subject Code Subject Credits
PROJ 8106 Project II 18
  Total 18



Total credit point for M.Tech Computer Science & Engineering is 72

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