B.Tech. Data Sciences

  • Offered by:
  • Specialisation:
    Data Science
  • Duration:
    4 years | 8 semesters
  • Campus:
  • Eligibility:
    (a) Must have successfully cleared the Higher Secondary Examination (Class XII) (Minimum 50% marks) with Mathematics, Physics and Chemistry.
    (b) Qualifying marks of JEE, KEAM (Kerala Engineering Architecture Medical) or equivalent examinations.
datascience

Location:

Onakkoor, Ernakulam

 

Why B.Tech. Data Sciences at CVV?

The B.Tech. in Data Sciences (DS) programme is designed to equip students with the skills and knowledge required to navigate the ever-expanding field of data science. It prepares them to become professionals who can effectively extract insights from data, drive informed decision-making, and contribute to the development and implementation of data-driven strategies in organisations. With the increasing demand for data scientists in the industry, this programme opens up exciting opportunities for students to make a significant impact in the world of data science. Students will learn the fundamental principles of artificial intelligence as well as the practical applications of data science, including statistical analysis, data visualisation, and predictive modelling.

The B.Tech. Data Science Programme is an exciting and interdisciplinary undergraduate degree programme that focuses on the rapidly growing field of data science. This programme is designed to equip students with the knowledge, skills, and practical experience needed to extract valuable insights from large and complex datasets and to make data-driven decisions across various industries and domains. The course provides students with a strong foundation in mathematics, statistics, computer science, and data analytics, along with specialised knowledge in data mining, machine learning, data visualisation, and predictive modelling.

The curriculum of the programme covers a wide range of topics, including data manipulation, exploratory data analysis, statistical modelling, data visualisation techniques, database management, big data analytics, and data ethics. Students learn to leverage tools and programming languages such as Python, R, SQL, and Hadoop to handle and analyse large datasets efficiently. They develop the skills to apply statistical and machine learning algorithms to solve complex problems and derive meaningful insights from data. Students will actively engage in initiatives that bridge the gap between technology and social responsibility.

Graduates of the B.Tech. Data Science programme have diverse career opportunities available to them. They can work as data scientists, data analysts, machine learning engineers, business intelligence analysts, data engineers, and consultants in various sectors such as finance, healthcare, retail, technology, and more. Moreover, the programme provides a solid foundation for pursuing advanced research and higher studies in data science and related fields.

Programme Structure

Semester I

Semester I

Course Name

Course Type

Credits

Engineering Mathematics – I

BS

4

Engineering Physics

BS

3

Problem Solving and Programming

ES

3

Communicative English

HS

3

Design Thinking

HS

2

Computer Engineering Workshop

ES

3

Problem Solving and Programming Lab

ES

2

Engineering Physics Lab

BS

2

Yoga

MC

0

Semester Credits

                                  22

 

Semester II

Semester II

Course Name

Course Type

Credits

Engineering Mathematics – II

BS

4

Engineering Chemistry

BS

3

Basic Electrical and Electronics Engineering

ES

4

Engineering Graphics (CAD)

ES

3

Computer Programming using C

PC

3

Life Sciences

BS

3

C Programming Lab

PC

2

Engineering Chemistry Lab

BS

2

National Service Scheme

MC

0

Semester Credits

24

 

Semester III

Semester III

Course Name

Course Type

Credits

Discrete Mathematical Structures

PC

4

Introduction to Data Analytics and Visualisation using R

PC

4

Computer Organization and Architecture

PC

3

Data Structures

PC

3

Environmental Engineering

ES

3

Universal Human Values II/Indic Knowledge Systems – Self Unfoldment

HS

3

Engineering Ethics

MC

0

Data Structure Lab

PC

2

R Programming Lab

PC

2

Semester Credits

24

 

Semester IV

Semester IV

Course Name

Course Type

Credits

Engineering Mathematics – III

BS

3

Operating System

PC

3

Data Visualisation using Tableau

PC

4

Object Oriented Programming Through Java

PC

3

Database Management Systems

PC

3

Constitution of India

MC

0

Programme Elective I

PE

3

Operating Systems and Java Lab

PC

2

Database Management Systems Lab

PC

2

Semester Credits

23

 

Semester V

Semester V

Course Name

Course Type

Credits

Design and Analysis of Algorithms

PC

3

Formal Languages and Automata Theory

PC

3

Microprocessor and Microcontroller

ES

3

System Software

PC

3

Open Elective I

OE

3

Professional Ethics/IKS Pride of India

HS

3

Summer Internship/Addon Course

PW

2

System Software Lab

PC

2

Microprocessor and Microcontroller Lab

ES

2

Semester Credits

24

 

Semester VI

Semester VI

Course Name

Course Type

Credits

Data Warehousing and Mining

PC

4

Graph Theory

PC

4

Computer Networks

PC

3

Program Elective II

PE

3

Program Elective III

PE

3

Open Elective II

OE

3

Statistical Analysis and Computing

PC

4

Mini Project

PW

2

Networking Lab

PC

2

Semester Credits

28

 

Semester VII

Semester VII

Course Name

Course Type

Credits

Compiler Design

PC

4

Program Elective IV

PE

3

Project Phase I

PW

4

Industrial Training/Internship/ Research Projects in National Laboratories/ Academic Institutions/Add-on Course/Seminar/MOOC/NPTEL

PW

2

Semester Credits

13

 

Semester VIII

Semester VIII

Course Name

Course Type

Credits

Information Retrieval Systems

PC

4

Project Phase II

PW

6

Semester Credits

10

 

Category and Credits

Category

Category Code

Credits CVV

Humanities & Social Sciences

HS

11

Basic Sciences

BS

24

Engineering Sciences

ES

23

Open Electives

OE

6

Programme Electives

PE

12

Programme Core

PC

76

Project

PW

16

Mandatory Courses

MC

 

TOTAL CREDITS

168

 

Higher Studies & Career Avenues

Higher Studies

  1. Master’s in Data Science or Business Analytics: Deepen your understanding of data science principles and gain advanced skills in analytics and interpretation.
  2. Ph.D. in Data Science: Pursue research opportunities, contribute to the field, and potentially become a professor or researcher in academia.
  3. MBA with a Concentration in Business Analytics: Combine business and data skills to take on managerial roles in data-driven decision-making.
  4. Specialized Certifications: Obtain certifications in specific tools and technologies used in data science, such as Python, R, SQL, Hadoop, or machine learning frameworks.

Career Avenues:

  1. Data Analyst/ Big Data Analyst: Analyze and interpret complex data sets to provide actionable insights, work with massive datasets, utilising tools like Hadoop and Spark to extract meaningful insights
  2. Data Scientist/Machine Learning Engineer: Build and deploy machine learning models, work on predictive analytics, and contribute to data-driven decision-making.
  3. Data Engineer: Develop, construct, test, and maintain data architectures, such as databases and large-scale processing systems.
  4. Business Intelligence (BI) Analyst: Use data to help businesses make informed decisions, create reports, and visualise data for stakeholders.
  5. Data Architect: Design and create the structure for large datasets, ensuring they are usable for analytical purposes.
  6. Quantitative Analyst: Apply statistical and mathematical models to financial and business problems. 
  7. Consultant in Data Science: Provide data-driven solutions and insights to clients in healthcare, business, government and private sector companies etc.

CVV INSTITUTE OF SCIENCE & TECHNOLOGY

Unique Features of B.Tech. Programmes at CVV

  • State-of-the-art academic and hostel facilities, brand-new computer centres, labs, classrooms and research space.
  • Specialised workstations and servers, high-performance computing clusters, and leading-edge software.
  • Expert teaching faculty focused on empowering students to deliver technological innovation and impact.
  •  Real-world projects, publication opportunities, and industry collaborations.
  • Year-round guest lectures on industry trends, emerging technology, career opportunities, and other topics by members of our global panel of industry and academic experts.
  • Opportunities for paid internships in India and abroad from year one onwards.
  • Collaboration with leading corporations to enable students to intern and engage in the future of technology.
  • Introduction to Indian Knowledge Systems (IKS) to empower the students holistically.
  • An opportunity to know the real “Me” through Yoga and Meditation.

Guest Lectures, Industry Exposure, Internships, and Placements

In the four years at CVV, the students will be continually exposed to a global panel of industry and academic experts through guest lectures. These lectures will cover a broad range of topics, including career development, technology, finance, market trends, entrepreneurship, and the skills needed to succeed in all facets of startups.

Leading companies have agreed to offer paid internships to CVV students in India and, for the lucky few, overseas as well. Students have the opportunity to participate in research projects and internships with industry partners, giving them invaluable practical experience. Upon completion of the programme, the very same companies will compete to employ CVV students. CVV’s Placement Office will help prepare students and guide them every step of the way, firmly rooted in the conviction that “Your Success is Ours, too!”

Our Laboratories

Our laboratories are equipped with the latest hardware and software tools necessary for the study and practical application of engineering today and in the future. They are provisioned with the latest desktops, high-performance computing clusters, and specialised software that is essential for the study of artificial intelligence, automation systems, data sciences, and other domains. Our laboratories are designed to foster collaboration and innovation, providing students with a stimulating environment that encourages research and innovation. Designed to simulate real-world conditions in the marketplace, by working in these labs, students will gain practical experience in developing intelligent systems that interact with the physical world.

Expert Faculty

Our faculty members are leading experts in their respective fields, with extensive experience in industry and academia. They use a variety of innovative teaching methods and pedagogies to cater to the different learning styles and needs of students. Our highly motivated faculty, many with teaching and working experience in the US, UK, Australia, and premier institutions in India, are passionate about teaching and research. They are committed to providing students with the best possible education and industry exposure.

They collaborate on research projects with leading technology companies and research institutions. Faculty use interactive lectures, group discussions, case studies, experiential learning, and hands-on projects to engage students and encourage critical thinking and problem-solving. They also provide individualised feedback and support to help students improve their understanding of the subject matter. The valuable insights and perspectives gained by CVV students are priceless. Students gain a practical understanding of the concepts and skills needed to succeed in their chosen field.

Professor
Associate Professor
Associate Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor

CVV-IST Location

CVV has built an exclusive state-of-the-art facility for students and faculty at Onakkoor in Ernakulam district, just 35 km from the Ernakulam Junction Station and 50 km from Kochi Airport.

With new academic blocks, hostel and dining facilities, and leading-edge computers and software in the lab, students and faculty will live and work on the campus set amidst a verdant hill station-like location that is very conducive to learning, engaged with events, and exciting for building a social and academic life. With access to a convenience store and other shops, the student will look forward to every day as a new adventure in life and learning.

For queries or clarifications, reach us at:

Faculty

×