Accelerated_Computer_Science_Fundamentals_Specialization

A set of practice and demo code of Accelerated Computer Science Fundamentals Specialization on Coursera

Course website:

https://www.coursera.org/specializations/cs-fundamentals

Course title:

Accelerated Computer Science Fundamentals Specialization Data Structures and Algorithms in C++.

Learn fundamentals of computer science while implementing efficient data structures in C++.

Table of content

Course_#1 :Object-Oriented Data Structures in Cpp

1. Week_1_Orientation_Write_a_cpp_program

• Introduction
• Local development environment, toolchain, and IDE installation
• Cloud development environment configuration
• C++ Standard Library
• C++ Classes

2. Week_2_Understanding Cpp memory model

• Variable, pointer, and memory
• Stack
• Heap
• New, delete, and memory management
• Basic control flow
• Header file and source file
• Project: Hello world

3. Week_3_Developing Cpp Classes

• Classes
• Constructor / Destructor
• Copy assignment operator
• Variable storage
• Introduction to un-initialized pointer, segmentation Fault, and un-defined behavoir
• Range-based loop

4. Week_4_Engineering Cpp software solution

• Recursive with implementation of Tower of Hanoi
• Template type and template classes
• Inheritance
• Project: Image processing

Course_#2 :Ordered Data Structures

1. Week_1_Orientation_Linear data structures

• Introduction
• Array
• Linked-list
• Time and space complexity analysis of Array and Linked-list
• Operation of Array and Linked-list
• Queue
• Stack
• Project: Linked list and Merge sort

2. Week_2_Introduction to Tree structures

• Tree terminology
• Tree Traversal
• Binary Tree
• Binary Search Tree
• Time and space complexity analysis of Tree search operation

3. Week_3_Advanced Tree Structures

• Balanced Binary Search Tree
• AVL Tree adn its analysis
• B-Tree introduction
• B-Tree operation: insert and search
• Project: Generic Tree and Tree Traversal

4. Week_4_Heap Structures

• Heap introduction
• Heap and priority-queue
• Heap variation: min-heap, max-heap
• Heap operation: insert, extract-min, build heap, heapify adjustment
• Time and space complexity analysis of Heap

Course_#3 :Un-ordered Data Structures

1. Week_1_Orientation_Hashing

• Hashing introduction
• Hashing function with examples
• Collision handling: separate chaining
• Collision handling: probing and double-hashing
• Time and space complexity analysis of Hashing
• Project: Unordered-map

2. Week_2_Disjoint-sets

• Disjoint-sets introduction
• Disjoint-sets teminology
• Naive implementation
• Up-tree, a better implementation
• Smart union & Path-compression
• Time and space complexity analysis of Disjoint-sets

3. Week_3_Graph

• Graph introduction
• Week_3_Graph terminology
• Graph representation: edge list
• Graph representation: adjacency matrix
• Graph representation: adjacency list
• Time and space complexity analysis of graph operation
• Project: Graph search

4. Week_4_Graph algorithm

• Graph traversal algorithm
• Breadth First Search (i.e., BFS ) Traversal
• Time and space complexity analysis of BFS
• Depth First Search (i.e., DFS) Traversal
• Time and space complexity analysis of DFS
• Minimal spanning tree (i.e., MST ) algorithm
• Kruskal algorithm
• Prim algorithm
• Shortest path algorithm
• Dijkstra algorithm
• Dijkstra algorithm's edge case
• Time and space complexity of Dijkstra algortithm
• Landmark path problem