Computer Science and Engineering with a specialization in Data Science spotlights the emerging focus area – ‘Data Science’, which deals with the processing of large quantities of complex data to extract meaning and enable intelligent decision-making. The applications include the functioning of autonomous cars, customer behavior predictions, product recommendations by companies like Netflix and Amazon, and Covid-19 (or such pandemic) outbreak models. Multinational companies from many domains, including finance, marketing, retail, IT, and banking are looking for Data Scientists. With applications unlimited, it offers excellent opportunities across the world both in industry and higher education.

Realizing that there are plenty of opportunities across the globe, SRU offers this program with a core objective being to learn how to get access to enormous data from various sources, and generate business value to it by using multiple technologies. It consists of three parts - Machine Learning, Big Data, and Business Intelligence. Graduates acquire problem-solving and analysis skills for tackling complex problems from different domains.

SRU presents the best practice-based approach to build student knowledge and skillsets to suit market demands. Several MoUs with large and small IT companies enable us to offer hands-on experiences in cutting edge technologies and help place students in MNCs with high-pay packages.

Students of this program will have an opportunity to work as iScholars at Center for Artificial Intelligence and Deep Learning (CAIDL) which helps to expand their intellectual horizons and make them industry-ready. A student can also explore other interdisciplinary research centers@SRU

Program &

its Features

The curriculum is designed in a way that the institution has tie-ups with foreign universities to pursue a semester abroad. Besides, on completion of three years of the B.Tech program, students can opt for an integrated Master’s program in a partner university, abroad.

Apply computing theory, languages, algorithms, mathematical and statistical models, and the principles of optimization appropriately to formulate and analyze data.

Apply the principles and techniques of data collection, database design, and administration in support of business processes and functions.

Invent and use appropriate models of data analysis, assess the quality of input, derive insights from results, investigate potential issues, organize big data sets into meaningful structures in line with data profiling and quality standards.

In collaboration with industry, placement and internship opportunities are available to the students as data scientists, data analysts, and data engineers.


Data Analysts

Data Engineers

Data Architect

Business Analyst

Data and Analytics Manager

Business Intelligence Manager