NM
Jul 6, 2020
Dear Team ,
Namaste Everyone !!
Excellent Course structure - ML, VR and NLP.
Great Learning Module Design by All Faculty.
Thanks to everyone!!!
PL
May 2, 2020
The teaching materials are well presented and clear.
Just that the level of this course is a bit not advanced enough.
By Neela M
•Jul 7, 2020
Dear Team ,
Namaste Everyone !!
Excellent Course structure - ML, VR and NLP.
Great Learning Module Design by All Faculty.
Thanks to everyone!!!
By Patrick L
•May 3, 2020
The teaching materials are well presented and clear.
Just that the level of this course is a bit not advanced enough.
By vignaux
•Nov 17, 2019
Great course with a lot of practice and smart meaning !
By Julio C
•Jul 30, 2020
Great training !!!
By Suryabrata D
•Jul 6, 2020
very Informative
By Takahide M
•Jan 4, 2023
Very Nice.
By Akarapu K
•Aug 12, 2024
Very good
By Холмухамедова З Б к
•May 30, 2022
Perfect
By BHAVANA g
•Sep 22, 2020
Its pretty difficult to follow up with this course. We must have a good knowledge on Neural n/ws prior starting this course.
By S M A J
•May 28, 2020
Good for using IBM tools
By Dennis L
•Aug 29, 2020
Theory Overview only
By David L
•Aug 26, 2020
Aspects of this course could be worked on with regards to smoothness, conceptual teaching and grammatical/spelling errors.
Much of the course had confusing terminology/grammatical forms which made multiple lessons difficult to understand. The video quality was, for the most part, very well done -- but some videos moved too quickly to follow (although it may just be my current level is too low).
I really enjoyed the case studies for the most part; they were challenging and informative, forcing you to learn yourself. There were a couple of areas where I would've appreciated more guidance, such as setting up the MLP/CNN at the end of Week 2. I had no idea that we needed to use a sparse-categorical-crossentropy loss function until I looked at the solution -- and I'm not sure other students would know the same.
Otherwise, it was a useful course.
By Markey S
•Oct 10, 2024
Too much time on Theory. Little practical work. The practical work is basic and not advanced. Misspellings in Material and Downloads indicate a poor attention to detail from instructors.