B.Tech CSE (Data Science) with academic support of IBM (4 Years)


4 Years

Fees Structure





Total Fee




The B tech CSE in Data Science with academic support of IBM empowers students with all the skills necessary to acquire and manage the data to conduct data-driven investigations and sophisticated analysis. This programmes trains the students with the skills that are required to analyze and predict solutions in various fields of development.

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International Business Machines (IBM) is one of the leaders in Artificial Intelligence solution providers around the globe and has been changing the architecture of the AI world since its inception



Eligibility Criteria

Candidate must have passed 10+2 examination or equivalent with PCM and with minimum 50% aggregate marks

Programme Details

Programme Highlights
  • Specifically designed curriculum in consultation with industry insiders and experts
  • Consistent mentoring by acclaimed academicians and top industry experts
  • Working at IBM Big Data Analytics Lab for real-world exposure to industry-relevant case studies
  • Learn and Grow with IBM Experts from Day One
  • Globally Valid Digital Certifications by IBM
  • Futuristic Engineering Kitchen and Research Units
  • Highly sophisticated laboratories equipped with cutting-edge tech apparatus
Programme Structure

Semester 1
Course Title Credit
Engineering Calculus
Clean Coding with Python
Engineering Physics / Engineering Chemistry
Engineering Drawing & Workshop Lab
Clean Coding with Python Lab
Engineering Physics lab / Engineering Chemistry lab
Environmental Studies & Disaster Management (Online Moodle)
Data Analysis with Tableau & KNIME

Semester 2
Course Title Credit
Linear Algebra and Ordinary Differential Equations
Data Visualization using Python
Engineering Chemistry / Engineering Physics
Basics of Electrical & Electronics Engineering
Data Visualization using Python Lab
Engineering Chemistry Lab/Engineering Physics lab
Basics of Electrical & Electronics Engineering Lab
Extension Activities(community engagement service)
Open Elective-1

Semester 3
Course Title Credit
Discrete Mathematics
Data Structures
Java Programming
R Programming for  Data Science and Data Analytics Lab
Data Structures Lab
Java Programming Lab
Open Elective -II
Life Skills for Professionals-I
Summer Internship/Project-I

Semester 4
Course Title Credit
Probability & Statistics
Analysis and Design of Algorithms
Database Management Systems
Introduction to Data Science
Analysis and Design of Algorithms Lab
Database Management Systems Lab
Life Skills for Professionals-II
Open Elective -III
Data Science lab
Minor project-I

Semester 5
Course Title Credit
Theory of Computation
Operating Systems 
Machine Learning with Python
Operating System Lab
Machine Learning with Python Lab
Life Skills for Professionals-III
Summer Internship/Project-II
Software Engineering

Semester 6
Course Title Credit
Computer Organization & Architecture 4
Department Elective -I
Computer Networks 
Introduction of Neural Network and Deep Learning 
Department Elective-I Lab
Computer Networks Lab
Introduction to Neural Networks & Deep Learning Lab
Competitive Coding Lab
Minor Project-II


Programme Outcomes

Engineering Graduates will be able to:

  • PO1Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • PO2Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  • PO3Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
  • PO4Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  • PO5Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
  • PO6The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  • PO7Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  • PO8Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • PO9Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • PO10Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  • PO11Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  • PO12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Programme Educational Objectives (PEOs)

  • PEO1 - To prepare graduates to become proficient data scientists by providing a comprehensive understanding of data science concepts and techniques, including statistical analysis, machine learning, and data mining.
  • PEO2 - To prepare graduates for successful careers in the field of data science by providing hands-on experience in using industry-standard tools and latest technologies.
  • PEO3 - To develop graduates' critical thinking, problem-solving, and research skills to enable them to apply data science techniques to solve real-world problems and contribute to scientific research in the field of data science.
  • PEO4 - To nurture graduates' personal and professional growth by instilling ethical values, leadership, effective communication, teamwork, and lifelong learning habits, to prepare them for leadership roles in the field of data science.

Programme Specific Outcomes (PSOs)

  • PSO1 - Demonstrate a comprehensive understanding of data science concepts and techniques, including statistical analysis, machine learning, and data mining.
  • PSO2 - Apply industry-standard tools and the latest technologies in data science to solve practical problems and perform data analysis effectively.
  • PSO3 - Utilize critical thinking and problem-solving skills to apply data science techniques in solving real-world problems and contribute to scientific research in the field of data science.
  • PSO4 - Demonstrate ethical values, effective communication, teamwork, leadership abilities, and a commitment to lifelong learning in the context of data science, preparing graduates for leadership roles in the field.

Who should Pursue

Students who have a strong aptitude for mathematics and statistics and want to apply their knowledge to solve complex problems using data-driven approaches, and are interested in working with large and complex datasets while simultaneously developing their insight into data should pursue B.Tech CSE with specialization in Data Science.

Sponsored MBA Degree

K.R. Mangalam University offers a Sponsored MBA Degree to all of the new KRMU students who are looking forward to getting enrolled in the UG courses. 
KRMU bears the total course fee of the deserving student. This is a golden opportunity for the students who wish to pursue MBA after their undergraduate studies.


The students who wish to avail and pursue a Sponsored MBA Degree from K.R. Mangalam University should be eligible as per the following eligibility criteria:
  • The student must be enrolled in an undergraduate course at KRMU and needs to score more than 8.0 CGPA
  • Students must clear all of the papers/exams across the tenure in the first attempt
  • The student must have 75% or more attendance during the whole course period
  • The student should not have any disciplinary charges against him/her during the whole period of their undergraduate degree

Financial Assistance

K.R. Mangalam University partnered with the leading banks to help you to finance your dream course through Education Loan. You only have to start repaying one year after finishing your course or six months after you get a job.


  • Quick and Instant
  • Includes tuition fees, books cost, hostel fees, airfare.
  • Concessional rate of interest.
  • Speedy disposal of loan applications
  • Availability of the loan across the country
  • Up to 100% loan with lower interest rate and zero processing fees
  • Repayment tenure ranging from 5-15 years.

Career Options

The demand for data science professionals is growing, and there are many job opportunities available for B Tech CSE in Data Science graduates in the industry such as finance, manufacturing, healthcare, retail, and technology that can offer you job security. After completing B.Tech. CSE with specialisation in Data Science students can grab the chance to work in well-respected companies like:

  • Supply Chain
  • Computer Science
  • Advanced Analytics
  • Artificial Intelligence
  • Network Analysis
  • Machine Learning
  • Management Consulting
  • Predictive Modeling


K.R. Mangalam University has tie-ups with multinational companies that recruit students every year. The top recruiters that hire students of KRMU are Amazon, Flipkart, Cognizant, Wipro, IBM, Infosys Deloitte, Walmart, Genpact, Accenture, Microsoft, and Reliance.


Yes, K.R. Mangalam University extends promising financial assistance in partnership with the major banks and firms including GrayQuest, ICICI Bank, IDFC FIRST Bank and Axis Bank.

Some of the top recruiters offering leading roles to B.Tech CSE in Data Science graduates are Deloitte, Walmart, Genpact, Accenture, Microsoft, and Reliance among others.

Yes, the students inclined to pursue the B.Tech CSE in Data Science programme, may be eligible for the scholarship in accordance with the terms and conditions.

The students seeking admission to B.Tech CSE in Data Science are required to fill out the Online Application Form and take the KREE Entrance Assessment Test. Upon successful clearance, the shortlisted students have to attend the Faculty-Led Interview for confirmed successful enrolment.

Some of the key study areas covered in the B.Tech CSE in Data Science curriculum include hands-on experience through practicums, lab work, and solving real-world problems. It also introduces students to the fundamentals of applied statistics, applied mathematics, and computer science that are necessary in the context of data science and its applications.


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