access

lifetime

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15 Hours

**Description**

- 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.

Loonycorn is comprised of four individuals—Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh—who have honed their tech expertises at Google and Flipkart. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students. For more details on the course and instructor, *click here*.
This course is hosted by StackSkills, the premier eLearning destination for discovering top-shelf courses on everything from coding—to business—to fitness, and beyond!

Details & Requirements

- Length of time users can access this course: lifetime access
- Access options: web streaming, mobile streaming
- Certification of completion not included
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: all levels

Compatibility

- Internet required

**Terms**

- Unredeemed licenses can be returned for store credit within 15 days of purchase. Once your license is redeemed, all sales are final.

- What this course is about
- You, This course and Us

- Data Structures And Algorithms - A Symbiotic Relationship
- Why are Data Structures And Algorithms important?

- Complexity Analysis and the Big-O Notation
- Performance and Complexity
- The Big-O Notation
- What is the complexity of these pieces of code?

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

- Stacks And Queues
- Meet The Stack - Simple But Powerful
- Building A Stack Using Java
- Match Parenthesis To Check A Well Formed Expression
- Find The Minimum Element In A Stack In Constant Time
- Meet The Queue - A Familiar Sight In Everyday Life
- The Circular Queue - Tricky But Fast
- Build A Queue With Two Stacks

- Sorting and Searching
- Sorting Trade-Offs
- Selection Sort
- Bubble Sort
- Insertion Sort
- Shell Sort
- Merge Sort
- Quick Sort
- Binary Search - search quickly through a sorted list

- Binary Trees
- Meet The Binary Tree - A Hierarchical Data Structure
- Breadth First Traversal
- Depth First - Pre-OrderTraversal
- Depth First - In-Order and Post-Order Traversal

- Binary Search Trees
- The Binary Search Tree - an introduction
- Insertion and Lookup in a Binary Search Tree

- Binary Tree Problems
- Minimum Value, Maximum Depth and Mirror (12:14)
- Count Trees, Print Range and Is BST

- Heaps
- The Heap Is Just The Best Way to Implement a Priority Queue
- Meet The Binary Heap - It's A Tree At Heart
- The Binary Heap - Logically A Tree Really An Array
- The Binary Heap - Making It Real With Code
- Heapify!
- Insert And Remove From A Heap

- Revisiting Sorting - The Heap Sort
- Heap Sort Phase I - Heapify
- Heap Sort Phase II - The Actual Sort

- Heap Problems
- Maximum Element In A Minimum Heap and K Largest Elements In A Stream

- Graphs
- Introducing The Graph
- Types Of Graphs
- The Directed And Undirected Graph
- Representing A Graph In Code
- Graph Using An Adjacency Matrix
- Graph Using An Adjacency List And Adjacency Set
- Comparison Of Graph Representations
- Graph Traversal - Depth First And Breadth First

- Graph Algorithms
- Topological Sort In A Graph (17:30)
- Implementation Of Topological Sort (6:56)

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

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

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

access

lifetime

content

15 Hours