B.Tech. | Computer Science & Engineering (Data Science)

Focuses on the study of artificial intelligence, machine learning, and data analytics Covers areas such as data mining, pattern recognition, neural networks, and natural language processing Emphasises both theoretical understanding and practical implementation of AI and ML techniques Includes projects and research opportunities to apply AI and ML in real-world scenarios

Duration

4 Years (8 Semesters)

Programme type

Full time

Programme Regulations

Programme Structure 2023

B.Tech CSE Data Science Programme Structure 2023

Eligibility Criteria

Candidate should have passed the 2nd PUC/12th/Equivalent Exam with a minimum of 45% of marks in Physics and Mathematics along with Chemistry/ Computer Science/Electronics/Information Technology/ Biology/ Informatics Practices/ Biotechnology/ Technical Vocational subject/ Agriculture/ Engineering Graphics/ Business Studies/ Entrepreneurship. (40% for Karnataka reserved category candidates) from a recognized board. Candidates must also qualify in one of the following entrance exams: CET/ COMED-K/JEE/Other state entrance tests /National level entrance test
OR
Passed D.Voc stream in the same or allied sector.

Key Features

Data Science have had an active and exciting history and are now mature areas of computer science.
Many of the research discoveries have now reached the point of industrial application, and many companies have made and saved millions of dollars by utilising the results of Data Science research (McKinsey Global Institute report on AI).
In order to acquire the right skill set for the upcoming job opportunities in the areas of Data Science, which can complement and assist the industry in adopting technology-driven solutions, CMR University is offering a wide spectrum of new-age IT programmes, with Data Science being one of them.
This first-of-its-kind B.Tech programme in Computer Science and Engineering with specialisation in Data Science (DS) is specifically designed to prepare students with theoretical foundations and practical skills in Data Science, equipping them to face the new world of digital disruption and transformation.

Scope and Objective

Artificial intelligence and Data Science has had an active and exciting history and is now a mature area of computer science.
Many of the research discoveries have now reached the point of industrial application and many companies have made and saved millions of dollars by utilizing the results of Data Science research ( McKinsey Global Institute report on AI).
In order to have the right skill set for the upcoming job opportunities in the areas of Data Science, which can complement and assist the industry in adopting technology-driven solutions, CMR University is offering a wide spectrum of new-age IT programmes and Data Science is one among them.
This first of its kind B.Tech programme in Computer Science and Engineering with specialization in Data Science (DS) is specifically designed to prepare students with theoretical foundations and practical skills of Data Science, to face the new world of Digital disruption and transformation.

Programme Structure

SEMESTER I

Fundamentals of Design I
Typography I
Visual Identity Design I
Layout Design I
Mini Project I
Introduction to Product Design
Mini Project II
Design Thinking I
Community Service I
Semester I Project

SEMESTER II

Drawing I
Introduction to Fashion Design
Mini Project III
Introduction to Interior (Space) Design
Mini Project IV
Oral and Written Communication
Arts & Philosophy
Community Service II
Personal Effectiveness
Semester II Project

SEMESTER III

Fundamentals of Design II
History of Art and Design I
Textile Design
Textile Science
Critical Inquiry
Ethics and Values
Community Service – III
Career Preparedness Program-I
Project III (Textile Styling)

SEMESTER IV

Interdisciplinary Elective I
History of Art & Design II
Fashion Theory & Design
Apparel Construction
Indian Constitution
Hindi / Kannada / English / FL
Community Service – IV
Career Preparedness Program-II
Project IV (Apparel Construction)

SEMESTER V

Interdisciplinary Elective II
History of Art and Design III
Traditional Indian Textile Art
Fashion Accessory
Draping
Design Management
Environment and Sustainability
Prepare for Aptitude Tests – III
Project V – (Accessory Design)

SEMESTER VI

Interdisciplinary Elective III
History of Art & Design IV
System Design
Research Methodology
CAD
Knitwear and Apparel Quality Control
Sociology of Globalization & Sustainable Development
Design Thinking – II
Career Preparedness Program-III
Project VI – (Wearable Tech)

SEMESTER VII

Interdisciplinary Elective IV
History of Art & Design V
Universal Design
Career Advancement
Project VII – (Design Intervention & Communication)

SEMESTER VIII

Graduation Portfolio
Exhibition
Graduation Project – (Specialization)

Programme Assessment

Choice-Based Credit System (CBCS): The university follows CBCS, which allows students to choose courses and earn credits based on their performance
Grades and GPA: Students are awarded grades for each course in a semester, and their Semester Grade Point Average (SGPA) is calculated to measure their academic performance. Cumulative Grade Point Average (CGPA) is used to evaluate the overall performance of a student across all semesters.
Prescribed Curriculum: Each program has a prescribed curriculum or Scheme of Teaching and Evaluation, which includes the required courses, laboratories, and other degree requirements. It also incorporates SWAYAM and Massive Open Online Courses (MOOCs) offered by reputed institutions.
Auditing Courses: Students have the option to audit courses, which allows them to gain additional exposure without the pressure of obtaining a grade. This can give them an advantage in placements.
Evaluation System: The evaluation of students is comprehensive and continuous throughout the semester. It consists of Continuous Internal Evaluation (CIE) and Semester End Examination (SEE). CIE and SEE carry equal weightage of 50% each, resulting in a total evaluation of 100 marks for each course, regardless of its credit value.
Assessment Methods: Before each semester, faculty members may choose assessment methods such as assignments, seminars, quizzes, group discussions, case studies, practical activities, class presentations, industry reports, etc., with suitable weightage for each.
Semester End Examination: A Semester End Examination is conducted for all registered courses at the end of each semester. However, some courses that already have Continuous Internal Evaluation may not require a SEE. Makeup Examinations: Students who fail the Semester End Examination in one or more courses are eligible for makeup examinations, which provide an opportunity to retake the failed exams and improve their grades.

Programme Outcome

Engineering Knowledge: Apply the knowledge of Mathematics, Science, Engineering Fundamentals, and an engineering specialization for solving complex engineering problems.
Design/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.
Conduct investigations of complex problems: Use research–based knowledge and research methods including Design of Experiments, Analysis and Interpretation of data, and synthesis of information to provide valid conclusions.
Modern 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.
The 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.
Environment 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.
Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the Engineering practice.
Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
Communication: 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 & receive clear instructions.
Project 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.
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.

Course Outcomes

B TECH (DS) Course Outcomes

What expertise will you gain?

Data science concepts and methodologies

Proficiency in programming languages

Machine Learning Algorithms

Data visualization

Insight-driven decision making

Career Opportunity

AI engineer
Machine learning engineer
Data scientist
Data analyst
AI consultant
Research scientist in AI and ML

Placements at

CMR University

200+ Recruiters, Pre-Placement modules from first semester focus on employability, emphasis on experiential learning, extensive focus on Internships, Training for competitive examinations – CAT, GRE, TOEFL, CMAT, Bank PO, and more.

Testimonials

"I loved the infrastructure of CMR University and its management. As a club coordinator I learnt how to manage team and the events helped me to grow my confidence level. I would like to specially thank the placement cell for guiding me and providing me a good platform (company) for my career."

Radheshyam Thakur

Course:BCA Placement at: IQVIA

How to Apply?

Step 1

Application
Enquiry

On-call guidance with step-by-step expert instruction on how to complete the application form.

Step 2

Offer
Letter

Provision of Offer Letter to commence further process.

Apply now