• Acads AI

Understanding Acads II- Learn WHAT matters the most!

This is the 2nd part of Understanding Acads series. For Part 1 Click here. Part 3 Click here


Prepared using AI and data driven algo, we bring to you the future of education: Compact Learning


Philosophy







A variation of Pareto Principle. Acads Rule states that with smart and targeted study of Acads Compact notes students can perform much better than trying to study bulky Books.


Compact Notes are an outcome of 5 step Process


Understanding the Process




1. High Yielding Topics (HYTs):

AI Algorithms scan previous year question papers to come up with topics that have been repeatedly asked in previous years questions of the said exam. Acads leverages Natural language processing to scan documents of over 40 years. Acads Engine is powerful enough to group similar terms together, enabling accurate assessment of “Yield” of a Micro-Topic

HYTs are Micro-topics that offer more than 4x return in comparison to an average microtopic. e.g. By investing 1 hour on a HYT you can secure more than 4x return in comparison to a random topic.


2. Topic Mapping

All HYTs and microtopics are than mapped to syllabus and arranged in a coherent and easy to understand manner by our team of experts comprising of IIT(Mostly B), IIM (Mostly A) and IXS Again, NLP comes to Acads rescue for effective mapping and makes the mapping more “scientific”


3. Note Making

Relevant and useful standard resources are scanned manually to filter out 70-90% of redundant information and to provide our learners with the Compact Notes


4. Reinforcement Learning

Notes are updated regularly using advanced AI algorithm of reinforcement learning. RL ensures that the Acads Engine learns by interacting with the consequence of its action

In Layman’s term, this means notes improves itself with changing exam pattern, syllabus and 45 other parameters


Mnemonics and Memory Tricks


Acads makes use of Mnemonics and Memory tricks to make the facts stick in the long term memory of our learners


PreBits


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