Department

COMPUTER SCIENCE AND ENGINEERING (Data Science)

Year of establishment: 2022
B.Tech. in Computer Science and Design (Data Science) (4 years) 
Year of commencement: 2022
Current Intake: 60

 

OVERVIEW

LABORATORIES

  • Artificial Intelligence Lab
  • Machine Learning Lab
  • Soft Computing Lab
  • Programming Language and Data Structure Lab
  • Networking Lab
  • Computer Architecture Lab
  • Data Science Lab

         

 

OVERVIEW

B.Tech in Data Science is a four-year undergraduate programme to provide an advanced learning opportunity for enthusiastic aspirants who wish to contribute to society by satisfying in-future industry demands for emerging skills and knowledge through interpreting data correctly, so that they can generate trend-setting ideas - today as well as in the future.

Digitalisation is the most important economic and social development of current time. Digital technology is significantly influencing our economy and at the same time satisfying all areas of interpersonal communication. It paves the way for new business models, with the help of consistent use of data, that were not previously possible. Data Science is therefore at the core of all digitalisation processes. This course aims at developing a strong engineering foundation with unique multi-disciplinary confluence of Computer Science, Computational Mathematics, Statistics and Management. After completion of this course, students will be able to demonstrate knowledge and skills related to data analytics, visualization, predictive modeling and analytics for data-driven decision making. The course will also include knowledge representataion. The course will also include knowledge representataion, machine learning and deep learning with relevant real-world applications.

Apart from core IT sector jobs, the students of B.Tech in CSE(Data Science) will have career opportunities in different private and public sectors with the following in-demand job roles:

  • Data Analyst
  • Data Engineers
  • Database Administrator
  • Machine Learning Engineer
  • Data Scientist
  • Data Architect
  • Statistician
  • Business Analyst
  • Data and Analytics Manager

PROGRAM EDUCATIONAL OBJECTIVES FOR B.TECH

After a few years of graduation, the graduates of B.Tech, CSE (Data Science) will

PEO 1: Be in regular employment in core IT industries or data science industries or will pursue higher studies or establish start-up companies.

PEO 2:  Continue demonstrating life-long learning ability by acclimating to emerging technologies and accepting challenges to serve the nation by solving short-term or long-term societal problems as an individual or as a part of a team.

PEO 3: Demonstrate effective communication skills and exhibit leadership skills for achieving professional advancement without violating professional code of conduct.

PROGRAM SPECIFIC OUTCOMES (PSOS)

On successful completion of the program, the graduates of B.Tech CSE (Data Science) will be able to:

PSO 1: Demonstrate fundamental knowledge and skills related to Data Science and relate them to real-world problems.

PSO 2: Apply fundamental statistical/mathematical methodologies and fundamental computational algorithmd to understand and design most elementary real-world problems related to data science and data engineering.

PSO 3: Integrate, analyze and visualize real world data by using modern tools for solving most elementary real-world problems.

PSO 4: Elaborate fundamental applications of data science in e-commerce, manufacturing, banking & finance, healthcare, transport and so on.

Vision

To transform the department into a centre of excellence for Computer Science and Engineering, through conscious, meaningful, devoted and determined effort of all the stake holders, by synergistic application of creativity, innovation, discipline and social consciousness.

Mission

To prepare the students for direct employment in various computer science and computer engineering related careers, pursuit of higher studies and / or research, or entrepreneurship in the field, by imparting them quality and value based education as per the needs of the society.

HOD Details

Dr. Saibal Majumder

B.Tech, M.Tech, Ph.D, PostDoc

Contact No:

Contact Email: saibal.majumder@bcrec.ac.in

 

Message from HOD

List of Faculty

Dr. Saibal Majumder Assistant Professor
INDRANIL SENGUPTA Assistant Professor

Achievements

Laboratories

Area of Research

Quantum Computing

Reversible Logic Synthesis

Machine Learning

Uncertainty Theory

Evolutionary Algorithms

IoT

Citation Network 

Faculty Activity

Publications
Journal
Name
Year
Cite as MLA/APA/Vancouver/IEEE Format
Dr. Saibal Majumder 2022 Haresh Kumar Sharma, Saibal Majumder, Arindam Biswas, Olegas Prentkovskis, Samarjit Kar, Paulius Skačkauskas (2022) A Study on Decision-Making of the Indian Railways Reservation System during COVID-19, Journal of Advanced Transportation (SCIE)
Dr. Saibal Majumder 2023 Criteria Selection of Housing Loan Based on Dominance-Based Rough Set Theory: An Indian Case (ABDC)
Dr. Saibal Majumder 2019 Uncertain programming models for multi-objective shortest path problem with uncertain parameters (SCIE)
Dr. Saibal Majumder 2019 A multi- objective multi-product solid transportation model with rough fuzzy coefficients (SCIE)
Dr. Saibal Majumder 2019 Type-2 Multi-Fuzzy Sets and their Applications in Decision Making (SCIE)
Dr. Saibal Majumder 2019 A method to solve linear programming problem with interval type-2 fuzzy parameters (SCIE)
Dr. Saibal Majumder 2018 Rough-fuzzy quadratic minimum spanning tree problem (SCIE)
Dr. Saibal Majumder 2018 Uncertain Multi-objective Chinese postman problem (SCIE)
Dr. Saibal Majumder 2018 Uncertainty based genetic algorithm with the varying population for random-fuzzy maximum flow problem (SCIE)
Dr. Saibal Majumder 2018 A new bi- objective fuzzy portfolio selection model and its solution through evolutionary algorithms (SCIE)
Dr. Saibal Majumder 2018 Uncertain multi- objective multi-item fixed charge solid transportation problem with budget constraint (SCIE)
Dr. Saibal Majumder 2018 Multi-criteria shortest path for rough graph (SCIE)
Dr. Saibal Majumder 2017 Cross-entropy based multi-objective uncertain portfolio selection problem (SCIE)
Dr. Saibal Majumder 2021 On type-2 fuzzy weighted minimum spanning tree (SCIE)
Dr. Saibal Majumder 2023 Saibal Majumder, Rintu Kutum, Debnarayan Khatua, Arif Ahmed Sekh, Samarjit Kar, Mitali Mukerji, Bhavana Prasher (2023) On intelligent Prakriti assessment in Ayurveda: a comparative study, Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 9827-9844 (SCIE)
Conference
Name
Year
Cite as MLA/APA/Vancouver/IEEE Format National/International
Dr. Saibal Majumder 2023 On Multi-objective Fuzzy Shortest Path Problem International
Dr. Saibal Majumder 2023 On multi-objective minimum spanning tree under the framework of uncertainty theory International
Dr. Saibal Majumder 2023 A design approach for traffic surveillance using real time computer vision for vehicle tracking International
Dr. Saibal Majumder 2023 Autonomous vehicle model for implementation and challenge in traffic observation and lane detection International
Book/Book Chaoter/Monogram/Edited Volume
Name
Year
Cite as MLA/APA/Vancouver/IEEE Format
Dr. Saibal Majumder 2022 Fuzzy Orienteering Problem Using Genetic Search eBook ISBN: 9781003307822
Dr. Saibal Majumder 2018 Mean-Entropy Model of Uncertain Portfolio Selection Problem eBook ISBN: 978-981-13-1471-1
Thesis Supervised

Student Activity