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CS-DS
Department

Computer Science & Engineering (Data Science)

The Department of Computer Science and Engineering (Data Science) is dedicated to imparting quality education in Data Science, Artificial Intelligence, Machine Learning, and emerging technologies through an effective teaching-learning process. The department focuses on developing students’ analytical, technical, and problem-solving skills through laboratory practice, projects, internships, workshops, hackathons, and industry interactions. It promotes research, innovation, lifelong learning, and entrepreneurship to prepare students for successful careers, higher education, and societal contribution. With a commitment to academic excellence and industry readiness, the department strives to nurture competent and ethical professionals capable of addressing real-world challenges through data-driven solutions.

  • Head of DepartmentHead of Department
  • Laboratories8 specialised labs
  • Experience15+ Years of Teaching, Research, and Academic Experience
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Vision

To empower Computer Science and Engineering (Data Science) students with knowledge and skills in Data Science and emerging technologies, fostering innovation, research, ethical practices, and sustainable solutions for societal development.

Mission

  • M1: To provide quality education in Computer Science, Data Science, Artificial Intelligence, and emerging technologies through an effective learning environment that promotes academic excellence and lifelong learning.

    M2: To equip students with analytical thinking, problem-solving abilities, ethical values, and professional skills to address industrial, societal, and global challenges using data-driven approaches.

    M3: To foster research, innovation, entrepreneurship, and industry collaboration for developing competent Data Science professionals who contribute to technological advancement and societal well-being.

Department at a Glance

  • AICTE Approved Intake60 seats
  • Affiliated to VTU, Belagavi
  • 8 Specialised Laboratories
  • Curriculum coversPython, R, SQL/NoSQL, Machine Learning, Deep Learning, Big Data, Cloud Computing, Data Visualisation, Statistics
  • Industry-aligned syllabus with internship and capstone project components

Key Focus Areas

  • Data Engineering & Pipeline Design
  • Machine Learning & Predictive Modelling
  • Big Data Technologies (Hadoop, Spark)
  • Cloud Data Platforms (AWS, Azure, GCP)
  • Business Intelligence & Data Visualisation
  • Natural Language Processing & Computer Vision
  • AI Ethics & Responsible Data Use

Program Outcomes (POs)

P01: Engineering Knowledge

Apply the knowledge of mathematics, natural science, computing, and engineering fundamentals and an engineering specialisation to the solution of complex engineering problems.

P02: Problem Analysis

Identify, formulate, and analyse complex engineering problems, reaching substantiated conclusions with consideration for the holistic nature of the problem.

P03: Design/Development of Solutions

Design creative solutions for complex engineering problems and design systems, components, or processes to meet identified needs with consideration for public health and safety, and cultural, societal, and environmental factors. Sustainability is intrinsic to design.

P04: Conduct Investigations of Complex Problems

Conduct investigations of complex engineering problems using research-based knowledge and research methods, including the design of experiments, analysis and interpretation of data, and synthesis of information to provide valid conclusions.

P05: Engineering Tool Usage

Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, recognising their limitations, to solve complex engineering problems.

P06: The Engineer and the World

Analyse and evaluate societal and environmental aspects while solving complex engineering problems, considering their impact on sustainability with reference to economy, health, safety, legal frameworks, culture, and the environment.

P07: Ethics

Apply ethical principles and commit to professional ethics, human values, diversity, and inclusion, and adhere to relevant national and international laws.

P08: Individual and Collaborative Team Work

Function effectively as an individual, and as a member or leader in diverse and multidisciplinary teams.

P09: Communication

Communicate effectively and inclusively within the engineering community and with society at large by comprehending and writing effective reports and design documentation, and making effective presentations, considering cultural, language, and learning differences.

P010: Project Management and Finance

Apply knowledge and understanding of engineering management principles and economic decision-making, and apply these to one’s own work, as a member and leader in a team, to manage projects in multidisciplinary environments.

P011: Life-Long Learning

Recognise the need for, and have the preparation and ability for independent and life-long learning, adaptability to new and emerging technologies, and critical thinking in the broadest context of technological change.

PROGRAM EDUCATIONAL OBJECTIVES (PEOs)

  1. : Strong Technical Foundation Graduates will demonstrate strong foundations in Computer Science, Mathematics, Statistics, and Data Science to analyze, design, and develop intelligent solutions for complex real-world problems.
  2. : Professional Competence Graduates will pursue successful careers in industry, higher education, research, and professional certifications through continuous learning to adapt to evolving technologies and industrial needs.
  3. : Innovation and Entrepreneurship Graduates will engage in research, innovation, and entrepreneurial activities by leveraging Data Science, Artificial Intelligence, and emerging technologies to develop impactful products, services, and startups.
  4. : Professionalism and Leadership Graduates will exhibit professional ethics, effective communication, leadership qualities, teamwork, and project management skills while working in multidisciplinary and multicultural environments.
  5. : Social Responsibility and Sustainability Graduates will apply Data Science knowledge responsibly to address societal and environmental challenges by developing sustainable, ethical, secure, and inclusive technological solutions that contribute to national and global development.

PROGRAM SPECIFIC OUTCOMES (PSOs)

PSO1: Data Analytics and Problem Solving

Apply the principles of Computer Science, Mathematics, Statistics, and Data Science to collect, process, analyze, and interpret data for informed decision-making and effective problem solving.

PSO2: Intelligent System Development

Design, develop, and deploy intelligent Data Science solutions using Machine Learning, Artificial Intelligence, Big Data Analytics, Data Visualization, Cloud Computing, and modern software engineering practices to address industrial and societal challenges.

PSO3: Research, Innovation, and Emerging Technologies

Apply research methodologies, innovation, ethical practices, and emerging technologies to develop scalable, secure, and sustainable Data Science solutions, while fostering entrepreneurship and lifelong learning to meet evolving technological needs.

 

 

 

 

 

 

Leadership

Message from the Head of Department

Head of Department
Head of Department Professor & Head, CS & Engineering (Data Science) Ph.D. 15+ Years of Teaching, Research, and Academic Experience of teaching experience

Our department is dedicated to providing quality education, fostering innovation, and promoting research in emerging technologies. We strive to create a student-centric learning environment that emphasizes technical excellence, ethical values, industry readiness, and lifelong learning.

With the support of experienced faculty and modern learning facilities, we encourage our students to develop strong analytical, problem-solving, and leadership skills while contributing to society through innovation and responsible engineering.

I warmly welcome you to our department and wish you a rewarding academic journey and a successful future.

 

Dr. Santhosh Krishna B V

santhoshkbv@btibangalore.org 

4Year B.E. Programme
8+Specialised Labs
VTUAffiliated & AICTE Approved
2010Established
Data Science & Analytics Lab laboratory

Laboratories & Facilities

  • Data Science & Analytics Lab
  • Machine Learning & AI Lab
  • Big Data & Cloud Computing Lab
  • Python & R Programming Lab
  • Deep Learning / GPU Lab
  • Data Visualization & Business Intelligence Lab
  • Database Management Lab (SQL, NoSQL)
  • Statistics & Probability Lab

Events

24April 2026

IDEATHON 2026-National Level Innovation Competition

Full Day   Bangalore Technological Institute

A national-level IDEATHON open to Engineering, Diploma and Management students,no coding required, just your idea. Themes: AI &…

24April 2026

IDEATHON 2026-National Level Innovation Competition

Full Day   Bangalore Technological Institute

A national-level IDEATHON open to Engineering, Diploma and Management students,no coding required, just your idea. Themes: AI &…

22April 2026

Bharat Environment Program-Earth Week 2026

22-29 April 2026   Bangalore Technological Institute

BTI participated in the Bharat Sustainability Campus Mission 2026,Earth Week organised by the Research Heights Foundation in association…

News & Updates

January 3, 2026

Planting Seeds in the Hearts of Preschooler

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January 2, 2026

Why children need a Healthy Environment thousand

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January 1, 2026

Full-day kindergarten in Alberta kindergarten saves families.

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Ready to build your career in CS-DS?

Join Computer Science & Engineering (Data Science) at Bangalore Technological Institute — industry-aligned learning, modern labs and strong placement support.

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