Admission open for 2026-27

UG and PG programs | B.E – CET : E139 | M.Tech – PGCET : T962 | MBA – PGCET : B186

ICEAS

Department Data Science

Overview

The Bachelor of Engineering in Computer Science & Engineering (Data Science) is a specialized undergraduate program. Data Science is an interdisciplinary field that employs scientific methodologies, techniques, and algorithms to transform vast datasets into actionable insights. It integrates principles and practices from mathematics, statistics, and computer science to offer computational solutions for real-world challenges abundant in data.

This specialization equips students with proficiency in the tools and systems utilized by Data Science Professionals, enabling them to develop intelligent models across various domains within Computer Science.

We provide a 4-year B.E. program in Data Science, encompassing core computer science courses alongside essential subjects related to Data Science. This program facilitates the acquisition of fundamental knowledge and skills in mathematics, network security, computer vision, programming, communication networks, and Data Science.

Vision

To produce skilled and socially conscious engineers in the field of Data Science to contribute to the advancement of both India and the global community.

Mission

To offer high-caliber technical education in computer science and engineering, as well as data science, by fostering an innovative and technologically resilient learning environment.

To nurture an industry-friendly environment by furnishing cutting-edge infrastructure to thrive in a data-driven world.

To empower students to deliver innovative and cognitive solutions leveraging their data analytical skills and advancements in high-performance computing.

To promote individuals with a strong sense of integrity and social responsibility.

Vision

To serve as a hub of excellence in Artificial Intelligence and Machine Learning, offering high-quality education and research that addresses the demands of both industry and society.

Mission

To attain academic excellence by implementing innovative teaching and learning methods.
To foster a culture of innovation, creativity, and research.
To improve job readiness through skill enhancement and fostering interaction between academia and industry.
To cultivate individuals with a strong sense of ethics and social accountability.

Data Science

Program : UG

Department : Data Science

Duration : 4 Years

Program Outcomes (POs)

Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
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 the 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 and 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.

Overview Of the Curriculum

3rd SEM

Mathematics for Computer Science
Data Structures and Applications
Digital Design & Computer Organization
Operating Systems
Data Structures Laboratory
Object Oriented Programming with Java
PHP Programming

4th SEM

Analysis & Design of Algorithms
Database Management Systems
Microcontrollers
Design and Analysis of Algorithm Laboratory
Discrete Mathematical Structures
Scala

5th SEM

Software Engineering & Project Management
Computer Networks (NS-2/3)
Theory of Computation
Data Visualization Lab
Principles of Artificial Intelligence
Mathematics for Machine Learning
Artificial Intelligence Laboratory
DBMS Laboratory with mini

6th SEM

Big Data Analytics
Artificial Intelligence & Machine Learning
Devops
Machine Learning Laboratory
Mobile Application Development Laboratory

7th SEM

Scalable Computing
Statistical Machine Learning for Data Science
Information & Network Security
IOT Analytics
Software Engineering

8th SEM

Data Security and Privacy
System Modelling and Simulation

ICEAS

Value Added Courses

Natural Language Processing

Principles of Artificial Intelligence

Mathematics for Machine Learning

System Modelling and Simulation

Skill development courses

Data Structures and Applications
Design and Analysis of Algorithms
PHP Programming
Database Management System
Java for Mobile Applications
Mobile Application Development Laboratory
Big Data Analytics

FAQ

What are the major job opportunities after a Data Science degree?

Graduates can work as Data Scientists, Data Analysts, Data Engineers, or BI Analysts in tech, finance, and healthcare sectors.

What is a B.Tech/B.E in Data Science?

It is a 4-year undergraduate engineering program focused on data analysis, programming, machine learning, statistics, and building intelligent systems using data to solve real-world problems.

What essential skills does the program focus on?

Key skills include data analytics, statistics, programming, data visualization, and cloud
computing.

What are the top companies hiring Data Science graduates?

Companies like IBM, Accenture, Deloitte, Amazon, and Google recruit Data Science professionals.

Does the college offer internships for Data Science students?

Yes, internships are offered in collaboration with data analytics firms, startups, and IT companies.

What are the important tools and technologies taught?

Students learn Python, R, Tableau, Power BI, Hadoop, Spark, and SQL.

How does the program prepare students for industry demands?

The curriculum combines theoretical knowledge with practical lab sessions and case studies on real datasets.

What are the core subjects in Data Science?

Subjects include Data Mining, Machine Learning, Data Visualization, Database Management, and Predictive Analytics.

Are students exposed to live projects?

Yes, students work on live industrial and research-based projects during their final semesters.

What are the eligibility criteria?

Students must complete 12th with PCM and qualify through CET, COMEDK, or other
recognized entrance exams.

Does the department encourage research and publications?

Yes, students are guided to publish papers and participate in international conferences on data analytics.

Are workshops held by industry professionals?

Yes, experts from leading companies conduct guest lectures and workshops.

Are students encouraged to participate in online courses?

Yes, MOOCs from Coursera, edX, and Udemy are integrated into the learning path.

What makes the Data Science program unique?

A balanced mix of analytics, programming, and real-world application distinguishes this program.

What are the placement prospects?

Average placement packages range between ₹5–10 LPA depending on skillset and company profile.

Are there special labs for Data Science?

Yes, dedicated Big Data Labs and Cloud Computing Labs are available.

Are students encouraged to participate in hackathons?

Yes, participation in Kaggle, Smart India Hackathon, and DataThon events is encouraged.

What kind of programming languages are taught?

Python, SQL, R, and Java are emphasized for analytical model development.

Is machine learning part of Data Science?

Yes, ML concepts are integral to Data Science, enabling automation of analytical processes.

What certification courses are recommended?

Students can pursue certifications like Google Data Analytics, AWS Data Analytics, and Tableau Specialist.

How does the department support placement preparation?

Through mock interviews, aptitude training, and resume-building workshops.

Are students exposed to cloud technologies?

Yes, training on AWS, Azure, and Google Cloud is integrated into the curriculum.

What higher education options exist after graduation?

Students can pursue M.Tech/MS in Data Analytics, Business Analytics, or AI.

Does the department promote innovation and startups?

Yes, students are encouraged to develop data-driven products and business models.

Are international collaborations available?

Yes, collaborations with global universities for data research and internships are available.

What is the duration of the program?

It’s a 4-year undergraduate program consisting of 8 semesters.

What are the emerging areas in Data Science?

Emerging fields include Data Engineering, Edge Analytics, and Responsible AI.

Are students guided for competitive exams like GATE?

Yes, coaching and support are provided for GATE and GRE aspirants.

What is the role of mathematics and statistics in Data Science?

They form the base for understanding data distributions, correlations, and model predictions.

Are students involved in community data projects?

Yes, data-based social impact projects are encouraged.

What soft skills are emphasized?

Communication, teamwork, analytical thinking, and presentation skills.

EVENTS

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MBA Students Industrial visit to Bangalore Metro stations(25-08-2023) to know the startup issues – Entrepreneurship opportunities and Challenges

MBA students Participated in the “Business plan-Inter collegiate competition” -ideate 2023 held in Koshys college(28-09-23)-To orient on Business Planning and Launching an Enterprise

Industrial visit to Coorg Coffee Estate -to make the aware Coffee industry and opportunities(27-29, October 23)

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