Computer Science and Engineering (Data Science)

"Transforming data into value"As the world entered the era of big data, Data science is high in demand domain and explains how digital data is transforming businesses and helping them make sharper and critical decisions. Effective data scientists are able to identify relevant questions, collect data from a multitude of different data sources, organize the information, translate results into solutions, and communicate their findings in a way that positively affects business decisions.

Data Science is an emerging area of Computer Science and Engineering (CSE). The B.Tech program in Computer Science and Engineering (Data Science) is specifically designed and offered by the department of Computer Science and Engineering in response to the rapidly developing field of Data Science from the year 2020 with an intake of 60.

B.Tech program in Computer Science and Engineering (CSE) was accredited by the National Board of Accreditation (NBA) successively for six consecutive terms in 2008, 2013, 2016, 2019, 2022 and 2025 and M.Tech program in Computer Science and Engineering for three consecutive terms in 2019, 2022 and 2025. The period of NBA accreditation validity for both, B.Tech program in CSE in Tier-I (Washington Accord) and M.Tech program in CSE is till 30 June, 2028.

A B.Tech program in CSE (Data Science) provides students with a comprehensive understanding of the theoretical foundations and practical methodologies used to collect, manage, analyze, and interpret large-scale data. By learning modern data science principles, analytical techniques, and computational tools, students develop the ability to generate intelligent, ethical, and data-driven solutions for real-world problems across various sectors.

Particularly the program covers, data science courses with key subjects that synthesize topics from computer science, statistics, machine learning, big data systems, and information visualization. Students gain strong foundations in areas of Data Mining and Warehousing, Machine Learning Algorithms, Big Data Management, Data Handling and Visualization, Database Systems, and Predictive Analytics.

The department has 14 academic laboratories, Object oriented programming with java laboratory, Programming for Problem Solving Laboratory, Operating Systems Laboratory, Data Structures Laboratory, Programming with Objects Laboratory, Design and Analysis of Algorithms Laboratory, Web Systems Engineering Laboratory, Database Management Systems Laboratory, Data Handling and Visualization, Applied Artificial Intelligence, Data Mining and Warehousing, Big Data Management, Distrusted Systems and Security Lab, and Machine Learning Algorithms Lab. The infrastructure and lab facilities are upgraded from time to time and provide good practical learning and innovative environment for the students and researchers.

The students are nurtured with a variety of active learning activities including and not restricted to class room teaching, presentations, video lectures, MOOC courses, minor / honors courses, experiential learning (Exeed) and online courses by faculty in the institute and across the globe.

Skills and Competences:

Considering the potential expertise, a Computer Science and Engineering (Data Science) B.Tech graduate should have at least four or more of the following competences:

• Understand, collect, clean, manage, and analyze large structured and unstructured datasets to extract meaningful insights
• Apply statistical, mathematical, and computational techniques for data-driven problem solving and predictive modelling
• Use modern data science tools and programming languages such as Python, R, SQL, and relevant libraries (NumPy, Pandas, Scikit-learn, Matplotlib)
• Build, evaluate, and deploy machine learning and deep learning models for classification, regression, clustering, and recommendation tasks
• Understand and work with big data ecosystems including Hadoop, Spark, distributed computing, and parallel processing
• Design and develop end-to-end data pipelines, including data acquisition, data warehousing, ETL/ELT, feature engineering, and automation
• Use advanced visualization tools (Tableau, Power BI, Matplotlib, Seaborn, Plotly) to create clear and effective data stories for decision making
• Understand database systems, data models, and querying techniques, including relational and NoSQL databases
• Apply exploratory data analysis, hypothesis testing, and statistical inference for analytical decision-making

Data Science is an interdisciplinary field of Computer Science, which continuously evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals should master the full spectrum of the data science life cycle and programming skills.

The principal purpose of Data Science is to find patterns within data. It uses various statistical techniques to analyze and draw insights from the data. From data extraction, wrangling and pre-processing, a Data Scientist must scrutinize the data thoroughly. A Data Scientist is responsible for collecting, storing and maintaining the structured and unstructured form of data.

Skills gained includes, creating algorithms and models to extract, process, visualize and find hidden patterns from the raw information. Data Extraction and Transformation, Statistical Analysis, Data Manipulation, visualization, Machine Learning, and predictive Modeling.These skills are required in almost all industries, causing skilled data scientists to be increasingly valuable to companies.

The department has well-equipped specialized laboratory facilities like Data Science, Programming with Objects, Database Management Systems, Web Application Development, Object Oriented Analysis and Design, Data Wrangling and Visualization, Foundations of Machine Learning, Natural Language Processing, Virtual Reality and Big Data and Analytics etc. The infrastructure and lab facilities are upgraded from time to time and provide good practical learning and innovative environment for the students and researchers.

The students are encouraged to participate in Hackathons / Projects / Internships to improve their practical knowledge. The department also organizes regularly co-curricular and extra-curricular activities for the all-round development of students such as seminars, workshops, group discussions, etc. The department imparts specialized training to students to pursue their career in core and other IT related streams through various skill development activities.