B.Tech in Computer Science and Engineering (Data Science)
is a four-year undergraduate program that started with an intake of 60 in 2022 and combines the study of traditional computer science with the principles and techniques of data science.
The program typically covers a broad range of topics in computer science, including data structures, algorithms, problem-solving techniques, programming languages, operating systems, and computer networks. In addition, the program may include courses on Data Science and Machine Learning (ML) topics such as statistical analysis, data visualization, database systems, data mining, data analytics, big data technologies, machine learning algorithms, business intelligence, and more.
In this program, the students have the great opportunity to gain practical experience through lab work, projects, internships, capstone projects, research and other experiential learning. It helps them to apply the concepts and techniques they have learned to real-world problems and gain hands-on experience working with large datasets and using data science tools and techniques.
Graduates of this program may work in various industries, including technology, finance, healthcare, retail, transportation, manufacturing, energy, agriculture, marketing, cyber-security, government and more. Opportunities like data scientists, machine learning engineers, business intelligence analysts, data engineers, software developers, or other roles involve designing and implementing intelligent systems. They may also pursue further studies in post-graduate programs in Data Science, AI, ML or related fields.
Some of the industries where data scientists are in high demand include:
- Technology: Technology companies, such as Facebook, Apple, Amazon, Netflix, Google, and other top tech companies, hire data scientists to work on various projects, including search algorithms, advertising systems, and recommendation engines.
- Finance: Financial institutions such as banks, hedge funds, and insurance companies use data science to support decision-making, detect fraud, predict customer behaviour and develop new financial products.
- Healthcare: Data scientists in healthcare are working on areas such as precision medicine, drug development, patient outcomes analysis, and medical imaging analysis.
- Retail: Retail companies use data science to analyze customer behaviour and sales data to improve marketing and inventory management, forecast demand and optimize pricing.
- Manufacturing and Automotive: Companies in these industries use data science for predictive maintenance, quality control and optimizing their supply chains
- Energy and utilities: Companies in this field use data science to optimize power generation, transmission, and distribution.
- Consulting: Data Science consulting companies work with clients from diverse fields, helping them to leverage data to improve their business operations and strategies.
- Government and non-profit: Data science is also applied in government and non-profit organizations for areas like policy-making, budget allocation and public welfare.
- Media and Advertising: Companies in media and advertising use data science to understand customer preferences and make better ad placement and targeting decisions.
- Cyber security: Companies and organizations that provide cyber security solutions use data science techniques to protect against data breaches, cyber-attacks and data theft.