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From 0 to 1: Data Structures & Algorithms in Java

Master the Fundamentals of How Computer Programs Organize & Manipulate Data

What's Inside

Data structures and algorithms? They’re standard Computer Science 101 topics, and ones you’ll master in this course. You’ll learn how common data structures organize information so it can be used efficiently, how algorithms work to manipulate this data, and more. Though this course is tailored to the Java programming language, you’ll emerge from it with a deep understanding of how any computer program works.

Master data structures & algorithms w/ 11 hours of content
Visualize common data structures & the algorithms applied to them
Identify & apply which data structure or algorithm is optimal for a particular situation
Calculate the time & space complexity of code
Use the Big-O notation to perform complexity analyses on algorithms
Understand how linked lists work
Build a stack w/ Java, construct a queue, etc.

Course Curriculum

What this course is about

You, This course and Us - 3:03
Start

Data Structures And Algorithms - A Symbiotic Relationship

Why are Data Structures And Algorithms important? - 15:06
Start

Complexity Analysis and the Big-O Notation

Performance and Complexity - 16:04
Start
The Big-O Notation - 16:48
Start
What is the complexity of these pieces of code? - 19:12
Start

Linked Lists

Linked Lists - The most basic of all data structures - 19:55
Start
Linked List Problems - 10:25
Start
Linked Lists vs Arrays - 10:29
Start

Stacks And Queues

Meet The Stack - Simple But Powerful - 15:42
Start
Building A Stack Using Java - 16:55
Start
Match Parenthesis To Check A Well Formed Expression - 11:23
Start
Find The Minimum Element In A Stack In Constant Time - 8:53
Start
Meet The Queue - A Familiar Sight In Everyday Life - 14:13
Start
The Circular Queue - Tricky But Fast - 19:46
Start
Build A Queue With Two Stacks - 17:32
Start

Sorting and Searching

Sorting Trade-Offs - 10:54
Start
Selection Sort - 15:26
Start
Bubble Sort - 14:44
Start
Insertion Sort - 14:34
Start
Shell Sort - 14:26
Start
Merge Sort - 19:25
Start
Quick Sort - 15:30
Start
Binary Search - search quickly through a sorted list - 11:36
Start

Binary Trees

Meet The Binary Tree - A Hierarchical Data Structure - 13:05
Start
Breadth First Traversal - 18:45
Start
Depth First - Pre-OrderTraversal - 14:37
Start
Depth First - In-Order and Post-Order Traversal - 13:53
Start

Binary Search Trees

The Binary Search Tree - an introduction - 9:51
Start
Insertion and Lookup in a Binary Search Tree - 17:02
Start

Binary Tree Problems

Minimum Value, Maximum Depth and Mirror - 12:14
Start
Count Trees, Print Range and Is BST - 14:41
Start

Heaps

The Heap Is Just The Best Way to Implement a Priority Queue - 17:17
Start
Meet The Binary Heap - It's A Tree At Heart - 12:41
Start
The Binary Heap - Logically A Tree Really An Array - 17:16
Start
The Binary Heap - Making It Real With Code - 7:40
Start
Heapify! - 19:35
Start
Insert And Remove From A Heap - 16:36
Start

Revisiting Sorting - The Heap Sort

Heap Sort Phase I - Heapify - 19:33
Start
Heap Sort Phase II - The Actual Sort - 17:44
Start

Heap Problems

Maximum Element In A Minimum Heap and K Largest Elements In A Stream - 15:56
Start

Graphs

Introducing The Graph - 15:42
Start
Types Of Graphs - 7:23
Start
The Directed And Undirected Graph - 14:31
Start
Representing A Graph In Code - 8:11
Start
Graph Using An Adjacency Matrix - 15:27
Start
Graph Using An Adjacency List And Adjacency Set - 17:55
Start
Comparison Of Graph Representations - 10:11
Start
Graph Traversal - Depth First And Breadth First - 14:58
Start

Graph Algorithms

Topological Sort In A Graph - 17:30
Start
Implementation Of Topological Sort - 6:56
Start

Shortest Path Algorithms

Introduction To Shortest Path In An Unweighted Graph - The Distance Table - 12:38
Start
The Shortest Path Algorithm Visualized - 14:15
Start
Implementation Of The Shortest Path In An Unweighted Graph - 6:19
Start
Introduction To The Weighted Graph - 3:29
Start
Shortest Path In A Weighted Graph - A Greedy Algorithm - 18:47
Start
Dijkstra's Algorithm Visualized - 14:14
Start
Implementation Of Dijkstra's Algorithm - 8:15
Start
Introduction To The Bellman Ford Algorithm - 8:40
Start
The Bellman Ford Algorithm Visualized - 11:22
Start
Dealing With Negative Cycles In The Bellman Ford Algorithm - 7:36
Start
Implementation Of The Bellman Ford Algorithm - 6:54
Start

Spanning Tree Algorithms

Prim's Algorithm For a Minimal Spanning Tree - 17:27
Start
Kruskal's Algorithm For a Minimal Spanning Tree - 8:43
Start
Implementation Of Kruskal's Algorithm - 7:34
Start

Graph Problems

Design A Course Schedule Considering Pre-reqs For Courses - 13:01
Start
Find The Shortest Path In A Weighted Graphs - Fewer Edges Better - 14:31
Start

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