B.Tech - Computer Science and Engineering (CSE)

The programme in Computer Science and Engineering is designed to provide students an overview of computing, an understanding of the concepts, principles and skills in their application and extension, and a practical experience in applied computing. The programme emphasises the fundamental principles underlying computing and helps develop an understanding of the engineering considerations involved in computing system design, implementation and usage. The programme builds a strong foundation in the mathematics of computing - logic, sets, relations and grammar.

Concentration Areas

  1. Big Data/Data Sciences
  2. Cyber Security
  3. Mobile Technologies & Applications.
  4. Cloud Computing
  5. Geographic Information Systems

Programme Outline

The B. Tech programme in Computer Science and Engineering (CSE) at NU is aimed at building a strong foundation in mathematical and algorithmic concepts. It has a strong industry linkage to make students industry-ready. It also includes sufficient depth of knowledge in CSE for those interested in higher studies. It offers adequate flexibility to students to pursue their own interests through electives and projects.


8 (4 Years)

Total Credits:


CSE Core Courses

48 credits

CSE Electives

20 credits

Industry Practice

20 credits

R&D Project

4 credits

Course Split







Strong Industry Linkage

Consistent with one of NU’s core principles, the hallmark of the B.Tech (CSE) is the strong industry linkage. Students study common courses across disciplines in the first year and undertake several fundamental courses in the second year.

The R&D Project component in the sixth semester is done at NU under faculty mentors. Selected students may opt for live projects in collaboration with industry partners for this component of the programme.

The eighth semester involves a compulsory six-month industry practice. Additionally, students may opt for the Data Science Programme which is a specialisation within the CSE B.Tech Programme conducted in collaboration with industry partners. Some courses are taught by experts from the industry.

Companies from which CSE students have received Industry Practice offers in the past include Amazon, IBM, PwC, MakeMyTrip, Cognizant, Freecharge, SAP, etc.

Data Science Programme

Data Science Programme in simple terms involves the extraction of knowledge from data, employing techniques and theories drawn from many fields within the broad areas of Computer Science, Mathematics and Statistics

Acknowledging the huge demands of Data Science Professionals in the industry today, the programme in Data Science has been designed to create trained Computer Science graduates to fulfill the requirements of the industry. The programme content is co-designed with an industry partner. Students are shortlisted by the industry partner at the beginning of sixth semester and go through a set of special electives during sixth and seventh semesters, offered in collaboration with the industry partner.

The eighth semester is used for an industry project which can be completed either at the industry site or in the campus under joint supervision of industry and faculty mentors. At the end of the programme, the successful candidates may be hired by the industry partner. Currently the industry partner participating in this programme is IBM. We are in talks with other well-known companies to get them on board.

“We are very impressed with both the skills and attitude of NU graduates who have gone through the Analytics and Cognitive (Data Science) programme. They demonstrate terrific aptitude and attitude towards learning. We need more such graduates and they are performing significantly above the mass hired engineering graduates we hire from the top engineering institutions. The curriculum for the program is jointly designed by IBM (Cognitive group) and NU faculty and reflects the dynamic and changing requirements in the market place.” Vijay Muralidaran, Data Science Leader, Cognitive & Advance Analytics CIC, IBM

Undergraduate Research

Our programme is flexible enough to allow students interested in higher studies and careers in industrial R&D opportunities to participate in research at the undergraduate level itself. B. Tech students have the opportunity to participate in R&D projects in the sixth semester as per the curriculum. Those interested can (optionally) also undertake projects under faculty guidance during the summer breaks. Also the Industry Practice in the eighth semester can be done in an R&D organization for those with a research bent of mind. Several of our undergraduate students co-author and present research papers at international conferences.


The Computer Science and Technology area at NIIT University has 13 full-time faculty members. Of them 8 hold Ph.D degrees and 5 others are pursuing Ph.D. at the moment. The Ph.D degrees of the faculty are from well-known universities like Calcutta University; Georg-August University, Goettingen, Germany; IIT Patna; Jawaharlal Nehru University, Delhi; McMaster University, Canada; Missouri University of Science and Technology, Rolla, Missouri, USA; Ohio University, Athens, Ohio, USA and University of Minnesota at Minneapolis, USA. The faculty comes with rich prior work experience in teaching, research, industry and the government. Their research has been published in several international journals and conference proceedings.

Professional Core Courses

  • Fundamentals of Computer Programming
  • Data Structures
  • Computer Networks
  • Object Oriented Programming
  • Design and Analysis of Algorithms
  • Computer Architecture and Organisation
  • Discrete Mathematics
  • Database Management Systems
  • Operating Systems
  • Software Engineering
  • Theory of Computation
  • Mobile Computing
  • Compiler Design
  • Introduction to Communication Systems

Professional Elective Courses

  • Artificial Intelligence
  • Artificial Neural Network
  • Introduction to Soft Computing
  • Statistical Modeling for Data Science
  • Advanced Communication Networks
  • High Performance Computing
  • Introduction to Linear and Nonlinear Optimisation
  • Wireless Sensor Networks and Applications
  • Computer Vision
  • Mobile Platform Programming
  • Web Intelligence and Algorithms
  • Machine Learning
  • Computational Geometry and Applications
  • Cyber Security
  • Game Theory
  • Data Mining
  • Introduction to Information Security
  • Modeling and Simulation
  • Information Retrieval
  • Natural Language Processing
  • Java Programming