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Currently, VTU Code provides models and previous year questions (PYQs), which are highly useful for students. However, it would be even more impactful to integrate a feature that uses AI/ML to predict potential exam questions by analyzing existing models and PYQs.
This feature could assist students in focusing on key topics and preparing effectively, especially for those aiming to secure a passing score. Implementing such a predictive system would add immense value to the platform and enhance its utility for exam preparation.
Looking forward to your thoughts on this suggestion!
The text was updated successfully, but these errors were encountered:
Currently, VTU Code provides models and previous year questions (PYQs), which are highly useful for students. However, it would be even more impactful to integrate a feature that uses AI/ML to predict potential exam questions by analyzing existing models and PYQs.
This feature could assist students in focusing on key topics and preparing effectively, especially for those aiming to secure a passing score. Implementing such a predictive system would add immense value to the platform and enhance its utility for exam preparation.
Looking forward to your thoughts on this suggestion!
The text was updated successfully, but these errors were encountered: