I am part of the 2nd batch of the Post Graduate Diploma in AI & ML.
I am still pursuing this course and can share my thoughts on how the course is for me as of now.
Advantages:
==================
1) You will get Degree from IIIT in AI. Most of the good companies in AI today will look out for a dedicated and prestigious degree with course work in AI and IIIT+UpGrad is bridging the gap and providing the same.
2) This is One of the few courses in India focusing heavily on deep learning models.
3) Prof. Raghvan and Prof. Dinesh of IIIT-B are teaching the ML modules and they are very good when coming to clearly explaining the concepts.
4) Many of the basic concepts are being taught to build good intuition of Machine Learning models. Mos of the basic maths required for developing intuition of the algorithm is covered. The complicated part or more advanced areas of math might not be touched in lectures always, rather given as an optional lecture or external links/resources are provided for anyone who wishes to pursue the details of the model further.
5) Session and modules by Industry experts where the focus is on industry case studies(like ecommerce buying patters, telecom churn, etc.) and how we apply our learned concepts of Analytics and Machine Learning to solve them.
6) There are projects at end of main modules where we are challenged to work on provided datasets independently, very much like how a data scientist works and come with interesting insights and build robust models. The work is evaluated by the TA's and feedback to improve on the same is also provided.
7) We do have basecamps where we meet industry experts at IIIT campus. This is usually held during week ends and is also conducted Live for students who are not able to visit the campus during this period.
8) Career support is provided as to how to build a strong profile as a data scientist.
9) UpGrad is very proactive with any issues faced by students before or during the course. In my batch, few of our batch mates faced issue w.r.t gradient descent and was communicated to UpGrad. The same lecture was later provided online live by Professor help student understand the concepts.
10) You have weekly assignments/graded questions/lectures to be completed at your own pace during the week.
Disadvantages
===================
1) This is a on-line platform, hence peer to peer interaction is limited to whatsapp groups and base camps. But I think any online course will have this limitation.
2) Lectures are recorded, so even though these are good and of high quality with importance being given on simplifying the concepts, still if you have any doubts we cannot ask them there itself during the lecture.
2) Doubt clearing is done on-line via discussion forums between peers with involvement of TA's to verify if the answers are correct. This is effective but somehow I feel this should additionally be done at face-to-face level as well during live online sessions or basecamps visits to IIIT. We have raised this request in batch 2, so future batches may have this benefit.
3) Since this is a course for working professionals, carrier placements are not provided as done in any degree courses.
4) Since this is a new course, there are continuous improvements being made to how the program can be delivered best. Hence Some of the modules had certain difficulties with respect to math understanding,etc. but these are being constantly improved by UpGrad.
5) You need to dedicate around 8-12 hourse weekly for this program depending on your pace. This is sometimes hard for working professional but I think this is necessary if you want to build strong foundation in this field.
Good to have
===================
1) This course, though starts from basic foundations, I feel if you have a background in data science, will help a lot.
2) This course does not seem to be an entry level program as a lot of focus of the program is on advanced modeling techniques like Deep learning, Reinforcement learning, Graphical models, etc. This is for people who want to go at a higher level like a senior data scientist, lead scientist, etc.