Core Algorithms Courseware
Basics
Defining the problem- Input
- Output
- Constraints
Understanding the problem domain
- Understand the data type
- Understand the storage & processor
- Data Sources
Algorithms Strategies
- Brute Force
- Iterative and Conquer
- Transform and Conquer
- Backtracking
- Recurrence Relation
- Divide and Conquer
- Greedy Method – Heuristic
- Dynamic Programming
Algorithms – Time & Space Complexity
- Time Complexity – It is complex!
- How do you measure time taken by a program?
- How do you formulate generic time measures?
- Logarithms – An understanding.
- Examples
Data Structures – Organize Your Data
- Arrays, Stack, Queues
- List
- Trees
- Graphs
Sorting & Searching
Search without sorting Sorting techniques- Insertion Sort
- Merge Sort
- Quick Sort
- Heap Sort
- Linear Search
- Binary Search
Programs
20 sessions each ~90 minutes| Sum of Integers | Finding a loop in a list | Quick Sort |
|---|---|---|
| Fibonacci Series | Stacks – CRUD | Linear Search |
| Palindrome | Queue – CRUD | Binary Search |
| Anagram | Simple Sort | Trees – CRUD |
| Linked List CRUD operations | s Insertion Sort | Graphs – BFS |
| Doubly Linked List CRUD | Merge Sort | Graphs – DFS |
Problems Solved
20 sessions each ~90 minutes| Regular Expression Matching | Sudoku solutio |
|---|---|
| Balanced Binary Tree | Heap sort |
| Spanning Tree | Radix sort |
| Prim’s MST | Multi string search |
| Kruskal’s MST | Flatten binary tree |
| Kth Largest element in a BST | Knuth-Morris-Pratt Algorithms |
| n-queens problem | A* algorithm |
| Longest SubString | Two-Edge connected graph |
| Three/Four Number Sum | Linked list palindrome |
| Cycle in a graph | Bridge Edge |
| Search sorted matrix | Alien Dictionary |
| Suffix Trie construction | Word search |
| Longest common subsequence | Reserved |
| Knapsack problem | Reserved |
| Dijkstra’s Algorithms | Reserved |
| Topological sort | Reserved |
Artifacts to have handy during the class:
- Notebook and Pen
- Java IDE or Your Fav Language IDE like Python IDE or C++ IDE
