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BE – CSE (Data Science)

Welcome to the Department of CSE -Data Science

Course Detials

  • Course Duration : 4 Years
  • Intake : 60
  • No. of Faculty : 3
  • Doctorates : 1
  • Ph.D. Pursuing : 
  • Technical Staff : 6

Undergraduate Program

CSE-Data Science and Engineering

The Department endeavors for academic excellence in CSE -Data Science and Engineering  through the student-centric innovative teaching-learning process, competent faculty members, efficient assessment, and effective use of ICT. With globally competent UG and research programs to impart current skills and industry trends relevant to the subject, the Department of CSE-Data Science is focused on training dynamic leaders who are qualified to take on the roles that the future demands. The Department is also constantly engaged in promoting collaborative research through Industry-Institute Interaction in the various verticals of CSE-Data Science and Engineering, transforming the engineering aspirants to a socially responsible, ethical, technically skilled, and value-added professional or entrepreneur.

To be a school of Excellence in Computing for Holistic Education and Research

  • Mission 1

Accomplish academic achievement in CSE-Data  Science and Engineering through student-centered creative teaching learning, qualified faculty members, assessment and effective usage of ICT.

  • Mission 2

Establish a Center of Excellence in a various verticals of CSE-Data science and engineering to encourage collaborative research and Industry-institute interaction.

  • Mission 3

Transform the engineering students to socially responsible, ethical, technically competent and Value added professional or entrepreneur through holistic education.

Department Activities
Extra Curriculum Activities
Knowledge
  • CSE-Data  Science and Engineering Graduates will have professional technical career in inter disciplinary domains providing innovative and sustainable solutions using modern tools.

Skills
  • CSE-Data  Science and Engineering Graduates will have effective communication, leadership, team building, problem solving, decision making and creative skills.

Attitude
  • CSE-Data  Science and Engineering Graduates will practice ethical responsibilities towards their peers, employers and society.

PSO 1

Ability to adopt quickly for any domain, interact with diverse group of individuals and be an entrepreneur in a societal and global setting.

PSO 2

Ability to visualize the operations of existing and future software Applications.

1. Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

2. Problem Analysis: Identify, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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.,/p>

8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

9. Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

10. 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.

11. 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.

12. 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.

7. 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.

8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

9. Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

10. 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.

11. 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.

12. 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.

Laboratory

Computer Networks
The objective of the lab are computer networks and progressive network infrastructures emphasizing the issue of the information transfer of the multimedia nature with the required quality of services parameters (QoS)
Computer Programming and Data structurers Lab
Lab introduces about Computer hardware components and software required for C programming language. The students will be able to enhance their analysing and problem solving skills and use the same for writing programs in C.
DBMS lab
Data Base Management System laboratory is equipped with oracle 10G application software to work with basic SQL commands like create, insert, delete and update along with aggregate function and also used to develop small data base applications
Electronic Circuit and micro-processors lab
The ADE laboratory enables students to get the practical experience in design, assembly and evaluation of following circuits using PSpice simulation tool Analog Components and circuits including 555 Timer and Operational Amplifier, Combinational logic Circuits, Flip Flops and their Operations, Counters and Registers using Flip FlopsS, ynchronous and Asynchronous Sequential Circuits
ML Lab
Machine Learning is a science that enables machines (especially computers) to learn from environments and make own decisions.The Machine Learning Laboratory (MLL) carries out research and develops different theoretical foundations for machine learning such as: Reinforcement Learning, Deep Learning, Statistical Learning Theory, Multi-agent Systems, Game Theory and Mechanism Design, Blockchains, Explainable and Fair AI
Network and Web Lab
The importance of the web as a medium of communication. Creating an effective web page, including an in-depth consideration of information architecture, analysing the usability of a web site, HTML and CSS, social media content into web pages, use web services for dynamic content.
Research Lab
Machine Learning is a science that enables machines (especially computers) to learn from environments and make own decisions.The Machine Learning Laboratory (MLL) carries out research and develops different theoretical foundations for machine learning such as: Reinforcement Learning, Deep Learning, Statistical Learning Theory, Multi-agent Systems, Game Theory and Mechanism Design, Blockchains, Explainable and Fair AI
Web Project Lab
Students are going to implement graphics application's using Opengl and animate real world problems and applications, we have a mini project included where the students should develop an application using the topics covered in the syllabus.emphasizing the issue of the information transfer of the multimedia nature with the required quality of services parameters (QoS)
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Newsletter

Department Activities

OUR CREW

Dr. Damodharan p

Professor & HOD

Ms. Chaithra KV

Assistant Professor

Ms Preetha Kamath

Assistant Professor

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