Computer Science & Engineering (Data Science)
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Established in 2023, the CSE (Data Science) Department at BIRTS is dedicated to developing highly skilled professionals who can thrive in the rapidly evolving field of Data Science. The department’s curriculum is designed to provide a comprehensive understanding of data-driven technologies, including data analysis, machine learning, artificial intelligence, predictive modeling, and data visualization. By combining rigorous theoretical foundations with hands-on, practical learning experiences, the program ensures that students are well-prepared to tackle real-world challenges.
Students actively engage with large-scale datasets, contemporary data tools, and advanced analytics platforms, enabling them to derive actionable insights and develop innovative solutions for complex problems. The department emphasizes industry-oriented projects, collaborative research initiatives, and experiential learning, fostering critical thinking, problem-solving skills, and adaptability in a professional environment.
Committed to innovation, research excellence, and continuous learning, the CSE (Data Science) Department equips students to excel in careers across Data Science, Business Analytics, Artificial Intelligence, and related domains. By instilling a strong foundation in both theoretical knowledge and practical expertise, the department ensures that its graduates are industry-ready and capable of contributing meaningfully to the fast-paced, data-driven global landscape.
Vision
To be a globally recognized centre of excellence in Data Science education and research, fostering innovation, ethical data practices, entrepreneurship, and sustainable data-driven solutions for societal and industrial advancement.
Mission
- To impart quality education in Data Science through outcome-based learning, experiential training, and interdisciplinary collaboration in computing and analytics.
- To promote research, innovation, and product development in data analytics, machine learning, big data technologies, and artificial intelligence to solve real-world problems.
- To inculcate ethical data handling, professional responsibility, and lifelong learning skills to meet global industry, research, and societal expectations.
- To strengthen industry–academia interaction and entrepreneurship for sustainable technological growth and knowledge dissemination.
| No. Seats | Duration | Eligibility Criteria |
| 60 | 4 Years | 12th Pass General/ OBC Category Student Having 45% Marks in PCM. 12th Pass SC/ST Category Students Having 40% marks in PCM. |
• Java / C++ / .Net Laboratory
• Operating System Laboratory
• Computer Networking Laboratory
• Computer Graphics & Multimedia Laboratory
• Database Management System Laboratory
• Soft Computing Laboratory
• Software Engineering & Project Management Laboratory
Semester | Syllabus | Scheme |
B.Tech CSE with Data Science | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/CSEData_Science170921041932.pdf | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/BTechDataScience131022123735.pdf |
Iv | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/IV_Sem_BTech_Data_Science230222083656.pdf | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/IV_sem_BTech_Data_Science_Scheme220422044411.pdf |
V | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/BTech%20V%20sem%20CSE-DS180823113359.pdf | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/BTechCSEDS131022010823.pdf |
Vi | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/VI_Sem_SY_Data_Science170123114331.pdf | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/Data%20Science%20VI%20sem%20scheme060123015516.pdf |
Vii | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/CSE-Data%20Science%20%20VII%20Sem%20Syllabus030823012826.pdf | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/CSE-Data%20Science110723021159.pdf |
viii | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/Data%20Science%20%20syllabus090124024152.pdf | https://www.rgpv.ac.in/UC/frm_download_file.aspx?Filepath=CDN/PubContent/Scheme/CSE-Data%20Science%20Scheme090124024121.pdf |
PO1: Engineering Knowledge
Apply knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to solve complex engineering problems and develop appropriate technical solutions.
PO2: Problem Analysis
Identify, formulate, review research literature, and analyze complex engineering problems using first principles of mathematics, natural sciences, and engineering sciences to arrive at substantiated conclusions.
PO3: Design / Development of Solutions
Design solutions for complex engineering problems and design system components or processes that meet specified needs with appropriate consideration for public health, safety, cultural, societal, and environmental factors.
PO4: Conduct Investigations of Complex Problems
Use research-based knowledge and methods, including design of experiments, data analysis, and interpretation of results, to investigate complex engineering problems and provide valid conclusions.
PO5: Modern Tool Usage
Create, select, and apply appropriate modern engineering and IT tools—including modeling, simulation, and data analytics tools—with an understanding of their limitations.
PO6: The Engineer and Society
Apply contextual knowledge to assess societal, health, safety, legal, and cultural issues and the responsibilities relevant to professional engineering practice.
PO7: Environment and Sustainability
Understand the impact of engineering solutions in societal and environmental contexts and demonstrate knowledge of sustainable development principles.
PO8: Ethics
Apply ethical principles, professional ethics, and responsibilities and adhere to engineering norms and standards in professional practice.
PO9: Individual and Team Work
Function effectively as an individual, and as a member or leader in diverse and multidisciplinary teams.
PO10: Communication
Communicate effectively on complex engineering activities with the engineering community and society at large through reports, presentations, documentation, and clear instructions.
PO11: Project Management and Finance
Demonstrate knowledge and understanding of engineering management principles and apply these to manage projects in multidisciplinary environments.
PO12: Life-Long Learning
Recognize the need for, and engage in, independent and life-long learning in the broadest context of technological change.
PEO 1: Graduates will establish careers in data analytics, business intelligence, AI, research, or pursue higher studies.
PEO 2: Graduates will analyze and interpret large datasets to develop data-driven decision-making systems.
PEO 3: Graduates will demonstrate ethical data governance, communication skills, and teamwork in professional practice.
PEO 4: Graduates will adapt to evolving data technologies through continuous learning and innovation.
PSO 1: Data Analytics & Modeling
Graduates will be able to collect, preprocess, analyze, and interpret structured and unstructured data using statistical methods, machine learning algorithms, and modern analytical tools.
PSO 2: Big Data & Intelligent Systems
Graduates will be able to design and implement scalable data-driven systems using big data frameworks, cloud platforms, and AI technologies for decision-making applications.
PSO 3: Ethical & Professional Practice
Graduates will demonstrate ethical data governance, cybersecurity awareness, effective communication, teamwork, and entrepreneurial mindset in professional environments.