
IIT Madras: Always Keeping a Tab Open on the Industry


Sujith Vasudevan, Managing Editor, 0
aimed at expanding access to digital education.
According to a press release from IIT Madras, these courses are designed to be interdisciplinary. Students from fields such as science, engineering, commerce, and the arts will be able to make use of this course. Most importantly, these courses are built for participants without prior experience in AI or programming. However, each program mandates around 25 to 45 hours of engagement and includes applied case studies and real-world datasets. The offered courses encompass a wide range of AI applications. For instance, AI in Physics explores the role of machine learning and neural networks in solving physics-related challenges, while AI in Chemistry delves into molecular predictions and chemical modeling using AI-powered tools. AI in Accounting introduces automation concepts relevant to accounting and finance. On the other hand, AI/ML using Python provides a foundational understanding of programming, machine learning, and statistical methods for effective problem-solving.
According to a press release from IIT Madras, these courses are designed to be interdisciplinary. Students from fields such as science, engineering, commerce, and the arts will be able to make use of this course. Most importantly, these courses are built for participants without prior experience in AI or programming. However, each program mandates around 25 to 45 hours of engagement and includes applied case studies and real-world datasets. The offered courses encompass a wide range of AI applications. For instance, AI in Physics explores the role of machine learning and neural networks in solving physics-related challenges, while AI in Chemistry delves into molecular predictions and chemical modeling using AI-powered tools. AI in Accounting introduces automation concepts relevant to accounting and finance. On the other hand, AI/ML using Python provides a foundational understanding of programming, machine learning, and statistical methods for effective problem-solving.