Introduction

The IIT Madras BS Degree in Data Science and Applications is a unique program offering a flexible and robust curriculum tailored for students from diverse academic backgrounds. Spanning multiple levels, this program enables students to gain expertise step by step, from foundational concepts to advanced applications. Let’s explore the courses at each level in detail, including their subject names and focus areas.

The IIT Madras Data Science program is divided into three main levels: Foundation Level, Diploma Level, and Degree Level. Each level builds upon the previous one, allowing students to progressively develop their skills. Here's a breakdown of the key courses and topics at each level

Foundation Level (1st Year)

Build essential skills in mathematics, statistics, programming, and communication.

The Foundation Level consists of 8 courses (32 credits), ensuring students are well-equipped with the basic tools needed for a career in data science.

Subjects:

1. Mathematics for Data Science 1 (4 credits) – Covers basic algebra, calculus, and mathematical concepts.

2. Mathematics for Data Science 2 (4 credits) – Focuses on linear algebra and matrices.

3. Statistics for Data Science 1 (4 credits) – Introduces probability and descriptive statistics.

4. Statistics for Data Science 2 (4 credits) – Explores inferential statistics and hypothesis testing.

5. Computational Thinking (4 credits) – Logical reasoning and problem-solving techniques using computational approaches

6. Programming in Python (4 credits) – Teaches Python programming, debugging, and coding practices

7. English 1 (4 credits) – Strengthens written and verbal communication skills.

8. English 2 (4 credits) – Enhances comprehension and professional communication abilities.

Minimum Duration to Complete Foundation Level :- 2 Terms (8 Months)

Exit Option: Students completing the Foundation Level earn a Certificate in Foundational Data Science.

Diploma Level (Year 2)

Objective: Focus on practical skills and intermediate-level concepts in programming or data science.

At this level, students can choose one or both of the following tracks:

Diploma in Programming (27 credits)

Focuses on programming skills, databases, and application development.

Subjects:

1. Database Management Systems (4 credits) – Learn to design and manage databases effectively.

2. Programming, Data Structures, and Algorithms using Python (4 credits) – Key programming concepts for solving complex problems.

3. Modern Application Development I (4 credits) – Basics of building applications using modern frameworks.

4. Modern Application Development I - Project (2 credits) – A hands-on project to apply the learned concepts.

5. Programming Concepts using Java (4 credits) – An introduction to object-oriented programming with Java.

6. Modern Application Development II (4 credits) – Advanced application development techniques.

7. Modern Application Development II - Project (2 credits) – Advanced project focusing on full application development.

8. System Commands (3 credits) – Understanding and using operating system commands.

Diploma in Data Science (27 credits)

Focuses on gathering, analyzing, and interpreting data for business and technical decisions.

Subjects:

1. Machine Learning Foundations (4 credits) – Learn the basics of machine learning models and algorithms.

2. Business Data Management (4 credits) – Managing and analyzing business-critical data.

3. Business Data Management - Project (2 credits) – Practical project focused on business data solutions.

4. Machine Learning Techniques (4 credits) – Advanced machine learning methods.

5. Machine Learning Practice (4 credits) – Implementing and testing machine learning models

6. Machine Learning Practice - Project (2 credits) – Real-world project showcasing machine learning techniques.

7. Business Analytics (4 credits) – Tools and techniques for effective business decision-making.

8. Tools in Data Science (3 credits) – Hands-on experience with essential data science tools.

Minimum Duration to Complete Both Diplomas :- 4 Terms (16 Months )

Exit Option: Students completing this level earn a Diploma in Programming or Diploma in Data Science (or both).

Or can continue to Degree level 

Degree Level (3rd & 4th Year)

Objective: Gain advanced knowledge and specialize in data science topics.

The Degree Level consists of core courses and electives, allowing students to delve deeper into data science concepts and applications.

Core Courses (Mandatory):

1. Software Engineering – Learn to design, develop, and maintain software systems.

2. Software Testing – Explore methodologies for ensuring software quality.

3. AI: Search Methods for Problem Solving – Techniques for problem-solving using artificial intelligence.

4. Deep Learning – Advanced neural network concepts and their applications.

Elective Courses

1. Algorithmic Thinking in Bioinformatics

2. Big Data and Biological Networks

3. Data Visualization Design

4. Special Topics in Machine Learning (Reinforcement Learning)

5. Speech Technology

6. Design Thinking for Data-Driven App Development

7. Industry 4.0

8. Sequential Decision Making

9. Market Research

10. Privacy & Security in Online Social Media

11. Introduction to Big Data

12. Financial Forensics

13. Linear Statistical Models

14. Advanced Algorithms

15. Statistical Computing

16. Computer Systems Design

17. Programming in C

18. Mathematical Thinking

19. Large Language Model

20. Introduction to Natural Language Processing (i-NLP)

21. Deep Learning for Computer Vision

22. Managerial Economics

23. Game Theory and Strategy

24. Corporate Finance

25. Deep Learning Practice

26. Operating System

Capstone Projects:

In addition to courses, students complete multiple projects, including a Capstone Project, to apply their knowledge to real-world problems.

Exit Option:

After Year 3: BSc in Data Science

After Year 4: BS in Data Science and Applications

Conclusion 

The IIT Madras Data Science degree program offers a well-rounded curriculum that gradually builds from foundational concepts to advanced applications. Whether you're starting with basic programming and statistics or diving into machine learning and artificial intelligence, the program is structured to ensure students gain practical knowledge and industry-relevant skills. With multiple exit points, the flexibility to choose elective courses, and hands-on project opportunities, the curriculum is designed to empower students to thrive in the data science field, regardless of their entry point into the program.

That's it for this blog, thank you for reading it till here,mind sharing this blog to your fellow batchmates !! 

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Anas Khan

Student at IIT Madras (BS) and a Tech Geek