Centre for Machine Intelligence and Data Science
Review by Kandarp Solanki
Motivation for undertaking minor
To be honest, the first reason to choose CMiNDS minor was its demand but I was reluctant to take it just because of that. Then I attended the session organised by UGAC regarding Minors and Electives which was quite informative in terms of the insights given by seniors who had actually completed minor or even a dual minor.
Overview of Minor
The compulsory courses are:
DS203 - Programming for Data Science (6 credits)
DS303 - Introduction to Machine Learning (6 credits)
After this you just need 3 courses which you can choose out of your interest. There are a lot of courses available majorly in different variety of baskets like application-based, theoretical courses.
These usually run in Slot-5, so I did not face any issues personally but yes, if you take up some course which runs in a different slot then you might need to reconsider your timetable.
The course is well organised and structured and if lectures are regularly attended, it is a cakewalk to fetch an AA in the courses. You might also want to consider reading up blogs and stuff to keep yourself updated with all the new tools you are getting equipped with.
In conclusion, a student should expect a first hand experience into the world of AI/ML and then might pursue a specialization in a field of his/her interest by taking the basket courses.
Prerequisites
As such your pre-requisites are the form of enthusiasm, zeal to learn new things quickly, a good mathematical foundation of linear algebra and some basic hands-on in a language (preferably Python). About the CPI cutoff for the minor, last year it was around 8.4~8.5 as far as I have the information but it may vary largely depending on the number of applicants for the minor.
Final Takeaways
Even if you don’t get a good grade, I am sure you will learn a lot over the journey and the best part is that you will learn things which are actually implemented in real-world issues. Peace! :)