IIT Madras Introduces Btech In Artificial Intelligence And Data Analytics

Artificial Intelligence has evolved in various fields from engineering and science to humanities disciplines so it is important to understand the multi-disciplinary connections to be successful. The B.Tech. in AI and Data Analytics is uniquely positioned to consider this concept. IIT Madras has launched a BTech program in Artificial Intelligence and Data Analytics, starting from the academic year 2024-25, with 50 seats available and admissions will be through the Joint Entrance Exam (JEE).  AI & Data Analytics (AIDA) is an exciting journey into the realms of data science and artificial intelligence. BTech AIDA is meticulously crafted to equip students with the key skills and knowledge necessary to thrive in the dynamic landscape of modern technology. This unique programme is designed to cultivate expertise in diverse facets of AI and data analytics, offering a panoramic view of its applications across industries.

Details of AI and Data Analytics Course

Math, Data Science, AI foundations and interdisciplinary applications are included in the course. It is offered by the Wadhwani School of Data Science and AI, built with the provision of Rs. 110 Crore by Mr. Sunil Wadhwani, a distinguished alumnus of IIT Madras and the Co-founder of IGATE and Mastech Digital.

Candidates will learn the complexity of speech and language technology and computer vision, besides exploring applications in control and detection and time series analysis. Students can learn the depth of personal passion and interest.

The Designated Curriculum

• The core curriculum is designed to provide a comprehensive foundation in AI and data analytics, covering various subjects.
• There will be fundamental courses in linear algebra and specialised modules in ML, deep learning, and reinforcement learning.
• The curriculum is segmented into four parts, The First is ‘Foundation in Sciences’ which deals with mathematics, sciences, and statistics, followed by ‘Modelling Techniques’ such as convolutional neural networks, deep net and so on, the third is ‘Training and Deployment of Models’ in which the algorithms will be covered and finally, ‘Domain Applications’ concluding everything together.
• An interface with the industry is strong regarding internships, UG Research, and the student will have a much brighter chance of getting practical experience.
• Practical experience is embedded into the curriculum through laboratory sessions, workshops, and real-world projects, students graduate not only with theoretical knowledge but also with hands-on expertise ready for immediate application in the industry.

Faculties 

The Wadhwani School of Data Science and AI is home to the Department of Data Science and AI, which brings together several faculty from several centres, working together on various exciting interdisciplinary problems in Data Science & AI. Having a diverse set of 40+ affiliate faculty and research fellows from all over the world strengthens our interdisciplinarity. 

Key Aspects of the Course

1. Mathematical Foundations: Thriving into the mathematical structure of data science and artificial intelligence, a strong groundwork for more advanced research and modelling.
2. ML / AI Models: Exploring the varieties of the spectrum of models, ranging from mathematical and statistical to network architectures and empowering students to find solutions to complex problems.
3. Algorithms and Statistical Inferencing: Learning the art of algorithmic design and statistical inference, is important for finding meaningful insights from vast datasets.
4. Programming Skills: The programming skills are altered for making cutting-edge data science and AI solutions, leveraging the latest tools and languages.
5. Data Acquisition and Pre-processing: Gaining knowledge about the intricacies of acquiring, pre-processing, and collecting data that is essential to ensure quality and relevance in analytical endeavours.
6. Systems Thinking: Systems thinking is a critical mindset deploying into machine learning solutions effectively within real-world contexts.
7. Mathematical Modeling and Simulation: Channeling the power of mathematical modelling, computational methods, and simulation techniques to solve complex systems.
8. Driving into Real-world Problems: Applying data analytics and AI techniques and tackling real-world challenges is a must in different domains and encourages innovation and future impact.

The department’s international collaborations provide a broader understanding and exposure to global trends and methodologies in AI and data science. The WSAI department also has rich access to state-of-the-art computational facilities, both in its research centres and the High-Performance Computing Environment at IIT Madras.