IDDD - Data Science
Data science is a cross-disciplinary field of study that employs statistical analysis, scientific computing, and various methodologies to uncover valuable information and understandings from diverse and sometimes chaotic data. It involves extracting knowledge and insights from structured and unstructured data, incorporating domain-specific expertise from relevant fields.
The objective of the Interdisciplinary Dual Degree program in Data Science is to offer foundational knowledge to students from diverse disciplines in data science and offer numerous avenues for specialization in specific aspects of data science through elective courses and projects. This program is designed to prepare students to become applied Data Scientists and also equip them for further advanced studies in the field.
Who is eligible to apply?
Any undergraduate student pursuing a B. Tech degree at IIT Madras, regardless of their discipline, can qualify for admission to this program, as long as they meet specific minimum academic criteria. The selection process for applicants will be determined by a cutoff based on their Cumulative Grade Point Average (CGPA). The CGPA cutoff is usually 8, but may vary with the number of students applying.
Curriculum and Courses
The curriculum consists of a foundational module that encompasses fundamental theoretical concepts of data science as well as the programming tools required. After completing this core component, students have the flexibility to select 3-4 elective courses from a provided list. These electives offer a combination of advanced theoretical or algorithmic subjects as well as applied data science topics. Students have the option to specialize in a particular application area or develop a more profound understanding of the fundamentals of data science, depending on their interests.
Some of the courses offered in this program are:
- Introductions to Data Analytics
- Mathematical Foundations for Data Science
- Data Analytics Laboratory
- Big Data Laboratory, and more
A total of 157 credits have to be completed, 85 of which are through projects. Students are anticipated to complete the 85-credit project during the summer following the 8th semester, as well as the 9th and 10th semesters. They have the flexibility to pursue internships during the summer and fulfill the summer project either during the regular terms or the summer after the 10th semester.
Collaborations
The program involves collaboration from several advanced centers, for an enriched learning experience such as:
- Robert Bosch Center for Data Science and AI (RBCDSAI)
- Initiative for Biological Systems Engineering (IBSE)
- Amex Lab for Data Analytics, Risk and Technology (DART)
- pCoE (pre-Center of Excellence) in Sports Science and Analytics
- pCoE in Network Systems Learning, Control, and Evolution
What are the future prospects?
The future of data science is filled with opportunities as businesses generate vast amounts of data. Advancements in technology will integrate data science with AI and machine learning, enabling more advanced analysis. Data science will become more accessible, fostering innovation from diverse backgrounds. It will find applications in healthcare, finance, marketing, and cybersecurity, creating specialized roles. Overall, the future of data science promises growth, innovation, and impact across multiple domains.
To get more information on the program, visit here.