B.Tech CS (Specialization in Data Science)
Big data is great opportunity to develop the next generation technologies to store, manage, analyze, share and Understand the huge volume of data that is generated in business, as Amount of data being produced and captured is ever increasing at an exponential rate.
International Data Corp. (IDC) forecasts that data generation will increase the 40 Zetta (or 40 billion terabytes) by 2020, 50 times more than what we had in 2010.
The enormous amount of data can be used by business enterprises to generate new insights, enable better decision making and improve the process in organizations. Business analytics refers to the analysis of data using statistical, machine learning and quantitative techniques with the purpose of understanding past performance of the business and generating new insights for the future.
In India, the analytics market is also expected to double between 2013 and 2018, according to a report published by NASSCOM recently. There will be a need for about 2 lakhs data scientists in India over the next few years, according to sources in Analytics Special Interest Group set up by NASSCOM.
Hence, the creation of trained industry –ready business analytics technocrat professionals is the need of the day.
B. Tech in Computer Science with a specialization in Data Science has been created typically to cater to the above requirements and also to ensure analytics study in the area of popular professional domains like Banking, Finance, Insurance and Retail sector.
|Semester-I||Semester – II|
|Mathematical Foundation for Data Science||Discrete Mathematics and Linear Algebra|
|Probability and Statistics||Object-Oriented Programming Using Java|
|Database Management System||Web Technology|
|Programming Concepts using C||Data Structures|
|Introduction to Data Science and Analytics||Statistical Analysis Using R|
|Interdisciplinary Course – I||Interdisciplinary Course – II|
|Semester-III||Semester – IV|
|Domain Foundation-I||Domain Foundation-II|
|Fundamentals of Banking, Financial Services and Insurance||Data Economics for Banking, Financial Services and Insurance|
|Fundamentals of E-Commerce and Retail Management||Data Economics for E-Commerce and Retail|
|Advanced Mathematics||Security and Privacy for Data Science|
|Operating System & Compilers||Big Data Technologies|
|Software Engineering & Quality Assurance||NoSQL Databases|
|Analysis and Design of Algorithms||Data Visualisation|
|Python Programming for Data Science||Extract, Transform and Load|
|Interdisciplinary Course – III||Interdisciplinary Course – IV|
|Semester-V||Semester – VI|
|Mathematics for Data Scientist -II||Web and Social Media Analytics|
|Artificial Intelligence||Internet of Things (IoT)|
|Cloud Computing and Operations||Machine Learning Techniques|
|Domain Advance-I||Domain Advance-II|
|Data Analytics in Banking, Financial Services and Insurance||Compliances and Risk Management in Banking, Financial Services and Insurance|
|Data Analytics in E-Commerce Management||Compliances and Risk Management in Retails and E-Commerce|
|Optimization in Analytics||High Performance Computing|
|Data Warehousing and Mining||Model Validation Techniques|
|Semester-VII||Semester – VIII|
|Industry Project||Industry Project|
|Open Elective||Open Elective|
|Core Elective – I||Core Elective – II|
The University has set up specialized IT Labs to enable the students to develop a strong foundation of the basics and build complex applications through extensive practical work and industry-sponsored projects.