I started with Nishit K. Sinha’s books, particularly for VARC and LRDI. His language and explanations are more student-friendly and less overwhelming than Arun Sharma’s, especially if you’re not from a quant-heavy background. His LRDI book is underrated. Later, I supplemented with mocks and sectionals from CATKing and Cracku. So, start with one author, but eventually shift to mock-based learning.

I tried Arun Sharma first, but it felt too slow for Quant, he repeats a lot of the same types. Pair it with previous year CAT papers from 1999-2008 and 2017-2023. Nothing beats actual CAT logic.

I did full self-study and scored 99+ last year. Here’s what worked: For QA, Arun Sharma is okay for basics but can be too repetitive and not always CAT-level. I found Sarvesh Verma's Quantitative Aptitude more structured. For LRDI, Nishit K. Sinha is decent, but honestly, nothing beats solving past CAT sets and sectional tests from TIME/IMS/CATKing. For VARC, I ditched books entirely and read editorials daily, plus solved 3 RCs a day from previous year mocks.