Algorithms Data Structures in Java #2 (+INTERVIEW QUESTIONS)

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Trie Data Structures (Prefix Trees)

Lecture 1: What are tries (prefix trees)?

Lecture 2: Prefix tree introduction – insertion and searching

Lecture 3: Prefix tree introduction – sorting

Lecture 4: Prefix tree introduction – autocomplete

Lecture 5: Prefix tree introduction – associative arrays

Lecture 6: Tries implementation I

Lecture 7: Tries implementation II

Lecture 8: Tries implementation III

Lecture 9: Tries implementation IV – associative arrays

Lecture 10: Tries implementation V – autocomplete

Lecture 11: Tries implementation VI – sorting

Lecture 12: Hashing based data structures and tries

Lecture 13: Applications of trie data structures

Chapter 3: Interview Questions – IP Routing with Tries

Lecture 1: Networking and the longest common prefix problem

Lecture 2: Longest common prefix implementation

Chapter 4: Ternary Search Trees (TSTs)

Lecture 1: What are ternary search trees?

Lecture 2: Ternary search tree visualization

Lecture 3: Ternary search tree implementation – insertion

Lecture 4: Ternary search tree implementation – search

Lecture 5: Ternary search trees implementation – traversal

Lecture 6: Recursion and stack memory visualization

Chapter 5: Interview Questions – Boggle Game

Lecture 1: What is boggle and how to solve it?

Lecture 2: Boggle game with ternary search tree implementation I

Lecture 3: Boggle game with ternary search tree implementation II

Lecture 4: Boggle game with ternary search tree implementation III

Chapter 6: Substring Search

Lecture 1: Brute-force search introduction

Lecture 2: Brute-force search implementation

Lecture 3: Rabin-Karp algorithm introduction

Lecture 4: Rabin-Karp algorithm implementation

Lecture 5: Knuth-Morris-Pratt algorithm introduction

Lecture 6: Constructing the partial match table

Lecture 7: Knuth-Morris-Pratt algorithm implementation

Lecture 8: Z algorithm introduction

Lecture 9: Z algorithm illustration

Lecture 10: Z algorithm implementation

Lecture 11: Substring search algorithms comparison

Lecture 12: Applications of substring search

Chapter 7: Strings

Lecture 1: Strings and the String Constant Pool (Intern Pool)

Lecture 2: String's immutability

Lecture 3: Strings and StringBuilders

Lecture 4: String reversion

Lecture 5: Suffixes

Lecture 6: Prefixes

Lecture 7: Longest common prefix

Lecture 8: Longest repeated substring problem

Lecture 9: Why are suffix tries and suffix arrays useful?

Chapter 8: Basic Sorting Algorithms

Lecture 1: Sorting introduction

Lecture 2: What is stability in sorting?

Lecture 3: Adaptive sorting algorithms

Lecture 4: Bogo sort introduction

Lecture 5: Bogo sort implementation

Lecture 6: Bubble sort introduction

Lecture 7: Bubble sort implementation

Lecture 8: Selection sort introduction

Lecture 9: Selection sort implementation

Lecture 10: Insertion sort introduction

Lecture 11: Insertion sort implementation

Lecture 12: Shell sort introduction

Lecture 13: Shell sort implementation

Lecture 14: Quicksort introduction

Lecture 15: Quicksort introduction – example

Lecture 16: Quicksort implementation

Lecture 17: Hoare's partitioning and Lomuto's partitioning

Lecture 18: What is the worst-case scenario for quicksort?

Lecture 19: Merge sort introduction

Lecture 20: Merge sort implementation

Lecture 21: Merge sort and stack memory visualization

Lecture 22: Hybrid algorithms introduction

Lecture 23: Non-comparison based algorithms

Lecture 24: Counting sort introduction

Lecture 25: Counting sort implementation

Lecture 26: Radix sort introduction

Lecture 27: Radix sort implementation

Chapter 9: Interview Questions – Sorting

Lecture 1: Interview question #1 – implementing TimSort algorithm

Lecture 2: Interview question #1 – solution