Department of
CSE Data Science
Vision
To build a strong technical environment and foster leadership and problem-solving abilities in the domain of Data Science, creating professionals capable of addressing social and technical challenges
Mission
- To equip and expose students with the latest tools and technologies.
- To instill critical problem-solving capabilities, leadership qualities, research capabilities and to prepare them for global challenges.
- To establish state-of-the-art laboratories and foster collaborations with leading industries in the field of Data Science.
Data Science is an interdisciplinary course which combines wide areas of statistics, analytics, visualization of data and Knowledge Extraction. In today’s technical world where data is growing exponentially, data science ensures that the huge incoming data is properly handled, efficiently analysed and extracts useful knowledge for business development.
In our department, we not only give emphasis on study but also make students ready for industry with practical exposure in Data Science. The department has a team of highly experienced and motivated faculty members who are in process of tuning the young minds to make them globally competitive.
Data science encompasses preparing data for analysis, including cleansing, aggregating, and manipulating the data to perform advanced data analysis. Those who practice data science are called data scientists, and they combine a range of skills to analyse data collected from the web, smart phones, customers, sensors, and other sources to derive actionable insights for business leaders.
NCET has been granted Autonomous status under VTU and the institution is accredited by NAAC with A+ grade.
Programme Education Objectives (PEOs)
- 1
PEO1: To work as Data Scientist with an ability to solve wide range of computational problems.
- 2
PEO2: To work effectively in a diverse and multi-disciplinary field, as a team member or leader to solve the societal problems.
- 3
PEO3: Engage in self-directed and lifelong learning, continuously updating their skills by adapting emerging techniques, advancing in research and higher studies.
Programme Outcomes (POs)
PO1: Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in Washington Accord Knowledge 1 (WK1) to Washington Accord Knowledge 4 (WK4) respectively to develop the solution of complex engineering problems.
PO2: Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)
PO3: Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)
PO4: Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions. (WK8).
PO5: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)
PO6: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7)
PO7: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)
PO8: Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.
PO9: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences
PO10: 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, and to manage projects and in multidisciplinary environments.
PO11: Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)
Programme Specific Outcomes (PSOs)
- 1
PSO1: Analyze complex computing problems and apply to derive appropriate solutions.
- 2
PSO2: Design, implement, and evaluate database-oriented, computing-based solutions that address a broad range of requirements in the field of Data Science.
- 3
PSO3: Communicate and work effectively within diverse teams and professional environments.
Academic Boards
Board of Studies (BOS)
9 Items| Course Name | B.E in Computer Science Engineering (Data Science) ( 4 Years ) |
| Intake | 60 |
| Accreditation | Institution is Accredited by NAAC with A+ Grade |
| Professional Society Membership | IEEE |
| Professional Activities | Student chapter Seminars, workshops and FDPs are conducted regularly |
Dr. Syed Naimatullah Hussain
Professor & HOD
"Data Science is an interdisciplinary course which combines wide areas of statistics, analytics, data visualization and Knowledge Extraction. In today’s technical world where data is growing exponentially, data science ensures that the huge incoming data is properly handled, efficiently analysed and useful knowledge is extracted for intelligent business development. This Programme helps students to build mathematical and engineering skills required to advance their career as a Data Scientist or Data Analyst. We at NCET CSE (Data Science) not only give emphasis on study but also make students ready for industry with more practical exposure, Through innovative teaching-learning process, a teamwork approach and leadership building experience, our students gain vital communication and critical-thinking skills. We provide a platform for the students to enhance their Employability skills through Industry Institute Collaboration. Data Science will revolutionize every industry in the near future. India has the opportunity to be the talent provider to the world for data science. Spurring data science-based innovation and establishing, data science-ready infrastructure will be critical for preparing India’s jobs and skills markets for a data science-based future. Keeping in mind the extraordinary importance of data science, we are committed to shaping the data leaders of tomorrow."
Dr. Syed Naimatullah Hussain
BE, M.Tech, Ph.D.
Expert in Software Engineering, Machine Learning, and Cloud Computing. Published 25+ papers in reputed international journals and conferences.
Dr. Chandrappa S
BE, M.Tech, Ph.D.
Professor with 14+ years of experience in AI, IoT, and Data Science. Published researcher and innovator passionate about modern computer science education.
Mr. Subhakar M
BE, M.Tech, (Ph.D.)
Skilled in Python, ML, NLP, IoT, and Web Technologies. Published 25+ papers and conducted multiple hands-on technical workshops.
Mr. R Radhakrishnan
BE, M.Tech, (Ph.D.)
Mr. Umesh B L
BE, M.Tech
Mr. Manoj Kumar R
BE, M.Tech, (Ph.D.)
Assistant Professor with 9+ years of experience in full-stack development. Skilled in AI, ML, Cloud Computing, and modern programming technologies.
Mrs. Nikhila M R
BE, M.Tech, (Ph.D.)
Skilled in AI, Cyber Security, and Data Analytics. Interested in intelligent systems and secure computing solutions.
Mrs. Sushma B S
BE, M.Tech
Focused on NLP, Deep Learning, and Artificial Intelligence. Passionate about research in intelligent computing systems.
Syllabus
Batch 2024
Academic Calendar
Course Files
Data Analytics Lab
Equipped with tools for big data processing and statistical analysis.
Data Visualization Lab
Focused on creating interactive dashboards and communicating data insights.