In this sprint, you will learn about number bases, character encoding, and how values are stored in memory. We'll also talk all about hash tables, a very powerful data structure for getting more performance and flexibility out of your algorithms. Finally, we'll look at optimizing searching through data, as well as the powerful programming technique of recursion.
This module will teach about RAM, number bases, fixed-width integers, how arrays are stored in memory, and character encoding. These basics allow you to better understand how other data structures are stored in memory and have an intuitive sense of the time complexity of specific data structures' operations.
In this module, you will learn about the properties of hash tables, hash functions, and how to implement a hash table in Python. Hash tables are arguably one of the most important and common data structures you use and encounter to solve algorithmic coding challenges.
In this module, you will learn about hash collisions and implement a complete hash table in Python that takes collisions into account.
This module will teach about logarithms, linear search, binary search, and recursion. This material sets the stage for learning about traversal techniques of trees and graphs. Additionally, using a binary search is a common optimization technique that may come up during a technical interview.
