Data Structures and Algorithms (C# code in GitHub)

Search, Sort, Binary Heaps, Binary Trees, Nary Trees (paired with C# implementations in an open source GitHub repo)

What you'll learn:

• Sort algorithms (bubble, insertion, selection, quick, merge, heap, radix), Search algorithms (linear, hash-table, binary, ternary, jump, exponential, fibonacci), Binary Search Trees, AVL trees, Red-Black trees, B-Trees, B+Trees, Min Binary Heap, Max Binary Heap, Min-Max Binary Heap

This course teaches a comprehensive list of basic and advanced data structures and algorithms, an essential topic of coding interviews at tech companies.

The course is paired with a C# GitHub open source project (username: PiJei, repository name:AlgorithmsAndDataStructures) where each algorithm is tagged with its space and time complexities (Big O), and tested for correctness with the exact same examples used in this course.

If you are a developer or a graduate student who is preparing for coding interviews at large tech firms as Google, Amazon, Facebook, Apple, Microsoft, or smaller high tech companies, you have landed in the right place. By attending this course you will learn the essential and complex data structures and algorithms, once and for all.

Some algorithms are taught over a medium size example such that the algorithm repeats itself several times until it is no longer complex and rather easily understood.

You are expected to maintain the knowledge gained via this course for a very long period of time. This is because this course makes heavy usage of animations , examples, and repetitions, which are the keys for deeply learning new topics.

The course has 45 lectures (~ 400 minutes) covering the following topics:

Search Algorithms:

1. Linear Search

2. Hash-Table Search

3. Jump Search

4. Exponential Search

5. Fibonacci Search

6. Binary Search

7. Ternary Search

8. Interpolation Search

Sort Algorithms:

1. Bubble Sort

2. Insertion Sort

3. Selection Sort

4. Quick Sort

5. Merge Sort

6. Radix Sort

7. Heap Sort

Binary Heaps:

1. Min Binary Heap

2. Max Binary Heap

3. Min-Max Binary Heap

   With these operations:

   1. Build

   2. Insert

   3. Delete

Binary Trees:

1. Binary Search Tree

2. AVL Tree

3. RedBlack Tree

   With these operations:

   1. Insert

   2. Delete

Nary Trees:

1. B Tree

2. B+ Tree

   With these operations:

   a. Insert

   b. Delete