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IIT Jodhpur · B.S. in Management & Technology · Semester 1

Algorithmic Thinking in Business

Revision for Algorithmic Thinking in Business: notes on 15 units, 401 practice questions with explanations, 116 flashcards and 122 common traps, plus timed mock papers marked like the real quiz (+1 correct · −0.25 wrong · 0 blank). Free, and it remembers what you get wrong.

Open ATB in the hub Practise questions

What's covered

  1. What an algorithm is

    The four terms · The ATM example, and why algorithms grow · Textbook: Intro to DSA, Types, and Big O · Textbook: Algorithm Planning and Design

  2. Pseudocode & data types

    Pseudocode · The four data types · Textbook: Intro to DSA, Types, and Big O · Textbook: Algorithm Planning and Design

  3. Properties of a good algorithm

    The five core technical properties · The four execution and design properties · Textbook: Algorithm Planning and Design

  4. Three types of algorithm

    Divide and conquer, greedy, dynamic programming · Textbook: Intro to DSA, Types, and Big O

  5. Arrays

    What an array is · The five operations, and their cost · Textbook: Linear Data Structures · Textbook: Linear and Binary Search

  6. Linked lists

    Linked lists · Textbook: Linear Data Structures

  7. Stacks

    Stacks — LIFO · Textbook: Linear Data Structures

  8. Queues

    Queues — FIFO · The four types of queue · Textbook: Linear Data Structures

  9. Algorithm analysis & Big O

    Algorithmic complexity and the three cases · Big O growth classes, as the lecture taught them · Big O of data-structure operations · Textbook: Intro to DSA, Types, and Big O · Textbook: Linear and Binary Search

  10. Computer memory basics

    Textbook: Linear Data Structures

  11. Trees

    Trees — the vocabulary · Depth and height · Tree traversals · Six types of tree · Binary search trees and AVL balancing · Heaps and priority queues · Textbook: Tree Data Structures

  12. Hashing & hash tables

    Hash functions and mod · Hash tables, collisions and chaining · Hashing for security: passwords and integrity · Textbook: Hash Data Structures

  13. Graphs

    Graphs vs trees · G = (V, E) and degree · Directed graphs and in/out-degree · Weighted, connected and cyclic graphs · Depth-first search (DFS) on a stack · Breadth-first search (BFS) on a queue · Textbook: Graphs

  14. Searching algorithms

    Linear search, binary search and BSTs · Jump search and exponential search · Hash-based search · Choosing a search algorithm · Textbook: Linear and Binary Search

  15. Blockchain

    Blocks, hashes and the chain · Merkle trees and decentralisation · Blockchain applications and limits

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