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COMPUTER SCIENCE AND ENGINEERING AT NU

B Tech - Computer Science Engineering (CSE) with emphasis on Digital Transformation Technologies

B Tech Computer Science

True to its commitment to the core principle of Industry Linked, NU has recognized the urgent need of the industry for next generation digitally skilled engineers. Responding to this need, it has upgraded its curriculum to incorporate Digital Transformation Technologies – a pool of digital technologies that will transform the way organisations are run.

According to a recent release by NASSCOM, the skills of the future would be Big Data Analytics, Cloud & Cybersecurity Services, IoT, Artificial Intelligence and many other Digital Technologies. A huge demand is foreseen for roles such as mobile app development, social media, data scientists & platform engineering. According to a McKinsey report on ‘Technology Jobs & the Future of Work’, digital technologies could contribute $550 billion to $ 1 trillion of economic impact per year in India by the year 2025. According to another renowned survey, 69% of IT leaders expect huge surge in the job market in the next 3 to 5 years due to digital technologies.

This has led NU to infuse the CSE curriculum with relevant digital technologies that will enable students to add immense value to the organisations they will join.

The B.Tech in CSE with emphasis on Digital Transformation Technologies has received instant endorsement by industry bodies such as NASSCOM.

“Nasscom is playing a critical role in evangelising digital opportunity for the IT sector, and we will support the industry in facilitating skilling and re-skilling efforts through disruptive models. The sector needs a workforce trained in futuristic digital technologies to transform themselves from IT services providers to digital-transformation partners. Higher education institutes can play a key role here and I would like to welcome the pioneering initiative from NIIT University in creating this new-age talent pool.”
Mr. Raman Roy, Chairman, NASSCOM

“The scenario is changing rapidly. One the one hand, new areas of work are opening up as technology embeds itself more deeply within different industries and at the same time, existing service lines are being transformed through increasing intelligent automation. I am leading a pan-industry taskforce on behalf of NASSCOM on ‘Skilling for the Future’ and in our estimate, at least 50% future jobs would need skills in new Digital Technologies such as Artificial Intelligence and Anaytics. It is commendable that NIIT University has identified this need and taken it upon itself to create a talent pool with new-age skill sets”
Mr. Mohit Thukral, Executive Council Member at NASSCOM

With industry backing of the B.Tech CSE curriculum with emphasis on Digital Transformation Technologies, B.Tech CSE students can look forward to take on leadership roles in digitally transforming organisations that is the need of the future.

Innovative Features in the B.Tech CSE with emphasis on Digital Transformation Technologies Curriculum

  • Will be powered by a project based learning methodology which enables the teacher and the group of students to mould the learning style dependent on the profile of the learners and create an environment to provide constructivism and collaborative learning.
  • The ‘flipped-classroom’ model and a unique mastery learning platform integrated into the project based learning approach.
  • Will be embedded with Full Stack Programming, Big Data, Machine Learning, Natural Language Processing, Artificial Intelligence and Internet of Things (IOT) curriculum to make it more industry relevant.
  • Industry experts will work as mentors, along with NU professors in guiding the students as per the specified methodology.
  • New students joining B.Tech CSE program will be able to avail the benefit of the new curriculum right from 1st semester.
  • Ongoing batches of students will be imparted accelerated sessions, making them industry-ready.

Concentration Areas

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

Programme Outline

NU B Tech in Computer Science with emphasis on Digital Transformation Technologies, is mainly focused on 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 Computer Science Engineering (CSE) for those interested in higher studies. B Tech in Computer Science with emphasis on Digital Transformation Technologies at NU also offers adequate flexibility to students to pursue their own interests through electives and projects.

Semesters

8 (4 Years)

Total Credits:

178

CSE Core Courses

48 credits

CSE Electives

20 credits

Industry Practice

20 credits

R&D Project

4 credits

Course Split

Lectures

61%

Tutorials

4%

Practicals

35%

Strong Industry Linkage

Consistent with one of NU’s core principles, the hallmark of the B Tech Computer Science programme offered by NIIT University is a strong industry linkage. Industry professionals will work as mentors along with NU faculty giving the dual advantage of academic rigor and industry relevance to students.

The R&D Project is a comprehensive component of NIIT’s B Tech Computer Science programme and is taken up in the sixth semester under faculty mentors. Selected students may opt for live projects in collaboration with industry partners to gain the maximum from this opportunity.

One full semester in the final year involves a compulsory six-month industry practice. Additionally, students may opt for the Data Science Programme which is a specialisation within the B Tech Computer Science 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

B Tech Computer Science 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. Students pursuing B Tech Computer Sciencehave 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. During the eighth semester of B Tech Computer Science, industry practice can be taken up in an R&D organization by those with a research bent of mind. Several of our undergraduate students co-author and present research papers at international conferences.

Faculty

Faculty in the B Tech Computer Science and Technology area at NIIT University are from well-known universities like IIT-ISM Dhanbad, 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.

The B Tech Computer Science programme by NIIT University consists of the following core and executive courses:

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
  • Introduction to Communication Systems
  • Multi-device Programming
  • Advanced Java Programming

Professional Elective Courses

  • Artificial Intelligence
  • Artificial Neural Network
  • Introduction to Soft Computing
  • Introduction to Internet-Of-Things
  • 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
  • Compiler Design
  • Microprocessors and Microcontrollers