To equip students with the key skills and knowledge needed to succeed in the dynamic landscape of modern technology, IIT Madras has launched BTech in AI & Data Analytics (AIDA). This program is designed to cultivate expertise in various facets of AI and data analytics, providing a panoramic view of its applications across industries.
At the heart of AIDA are nine key outcomes, each serving as a pillar on which students will develop their skills: They include:
Mathematical foundations: enabling students to delve deeper into the mathematical foundations of data science and artificial intelligence, laying a solid foundation for advanced analysis and modeling.
ML/AI models: Invite students to explore a range of models, from mathematical and statistical architectures to network architectures, allowing students to develop sophisticated solutions to complex problems.
Learning Algorithms and Statistical Inference: The art of algorithmic design and statistical inference, essential for extracting meaningful insights from large data sets.
Programming skills: Hone your programming skills suited to creating cutting-edge data science and AI solutions, leveraging the latest tools and languages.
Data acquisition and preprocessing: Learning the intricacies of data acquisition, preprocessing, and curation is essential to ensuring its quality and relevance in analysis efforts.
Systems thinking: Cultivate a systems thinking mindset crucial to effectively deploy machine learning solutions in real-world settings.
Mathematical modeling and simulation: Harness the power of mathematical modeling, computational methods and simulation techniques to simulate and analyze complex systems.
Application to real-world problems: Apply data analytics and AI techniques to address real-world challenges across diverse domains, driving innovation and impact.
Fair and responsible AI: Adopt principles of fairness and accountability in the development of AI, ensuring ethical and equitable deployment of the technology.
Students will be allowed to tailor their learning path across a wide range of elective courses within and outside the department. From exploring the intricacies of speech and language technology and computer vision to exploring control and sensing applications and time series analysis, students have the opportunity to explore areas of personal passion and interest.
Program Components
The detailed curriculum includes topics such as Foundations of Linear Algebra, Calculus for Engineers, Programming and Data Structures, Programming Lab, Basics of Engineering Principles, Ecology and Environment , Computational Methods for DS, Algorithms for Data Science, Artificial Intelligence, Machine Learning II, Deep Learning among others.
