Bhuvnesh

In-depth study notes for Foundation of Probability and Statistics. Covers fundamental probability concepts, conditional probability, Bayes' theorem, discrete/continuous random variables, statistical inference, and hypothesis testing. Includes solved practice problems and key formulas for fast revision.

Comprehensive and easy-to-understand study notes for Linear Algebra and Its Applications. Covers vectors, matrix operations, systems of linear equations, determinants, vector spaces, eigenvalues, and eigenvectors. Perfect for computer science and data science students preparing for exams and coursework.

In-depth and well-structured study notes for Big Data Analytics (BDA). Covers key concepts including Hadoop ecosystem, MapReduce framework, Apache Spark, NoSQL databases, data mining techniques, and distributed storage systems. Packed with clear explanations, diagrams, and solved practice questions—perfect for course preparation, assignments, and exam revision.

Complete and well-structured study notes for Algorithmic Thinking and Its Applications (ATA). This document includes in-depth coverage of fundamental algorithm design strategies, time and space complexity analysis (Big-O notation), core data structures, searching and sorting algorithms, dynamic programming, and recursion. Packed with solved examples, clear diagrams, and practice questions, making it an ideal resource for quick revision, assignments, and exam preparation.

Complete 4-in-1 study bundle covering Probability & Statistics, Linear Algebra, Big Data Analytics, and Algorithmic Thinking. Includes detailed lecture notes, key formulas, solved practice problems, and exam revision guides for all 4 core subjects.