Are you ready to master Data Structures and Algorithms (DSA) using Python? This course is designed to equip you with the essential skills to write time- and memory-efficient code, which is crucial in today’s technology-driven world. DSA knowledge is not just a technical requirement; it’s a key differentiator in coding interviews and assessments at prestigious companies like Google, Amazon, Microsoft, and Meta. By mastering DSA, you can significantly enhance your prospects of landing a software development role in these top-tier organizations.

We will also work on two projects:

1. Dynamic Route Planner - Design and implement a route-planning system that calculates the shortest path between locations on a map (graph nodes) for delivery services. The system dynamically adjusts routes based on new delivery points or road conditions (e.g., traffic delays).
2. Single User Chat With Autocompletion - Build a real-time CLI chat application where a user can send messages and get autocompletion suggestions based on a dictionary of commonly used phrases or past messages of the user.

Here’s a comprehensive syllabus that will take you from foundational concepts to advanced techniques:

1. Introduction
   • Discover the importance of DSA in coding.
   • Learn basic Python skills tailored for DSA.
   • Understand Big O Notation to assess algorithm efficiency.
2. Arrays and Strings
   • Dive into arrays: their operations and multi-dimensional forms.
   • Explore strings with basic manipulations, substrings, and pattern matching techniques (e.g., KMP Algorithm).
3. Lists and Linked Lists
   • Examine the structure and functionality of Singly, Doubly, and Circular Linked Lists.
   • Develop essential operations (Insertion, Deletion, Traversal, Reversal) with hands-on practice.
4. Stacks and Queues
   • Master stack implementation using lists and linked lists, including applications like balanced parentheses and postfix evaluation.
   • Learn about various queue types: Simple, Circular, and Priority Queues, alongside Deque (Double-Ended Queue).
5. Recursion
   • Get to grips with the fundamentals of recursion and explore tail recursion.
   • Compare recursion and iteration through practical examples (Factorial, Fibonacci, Tower of Hanoi).
6. Trees
   • Understand binary trees, their traversals (Inorder, Preorder, Postorder), and Binary Search Tree operations (Insertion, Deletion, Search).
   • Delve into advanced topics like AVL and Red-Black Trees, as well as heaps and applications like Huffman Encoding.
7. Graphs
   • Learn graph representations (adjacency matrix, list) and explore graph traversals: BFS and DFS.
   • Study shortest path algorithms (Dijkstra, Bellman-Ford) and Minimum Spanning Trees (Prim’s and Kruskal’s), along with their applications.
8. Hashing
   • Understand hash tables and functions, collision resolution techniques, and real-world applications such as anagram detection and frequency counting.
9. Searching and Sorting
   • Compare searching algorithms (Linear and Binary Search) and sorting algorithms, including Bubble, Insertion, Selection, Merge, Quick, and Heap Sort.
10. Dynamic Programming
    • Explore the fundamentals of Dynamic Programming (Memoization vs. Tabulation) through real-world problems such as Fibonacci sequences and the Knapsack Problem.
11. Greedy Algorithms
    • Grasp the principles of the greedy strategy while tackling problems like Activity Selection and Minimum Spanning Trees.
12. Backtracking
    • Learn the basics of backtracking through engaging challenges like the N-Queens Problem and Sudoku solvers.
13. Advanced Data Structures (Optional for Beginners)
    • Explore advanced structures like Tries, Segment Trees, Fenwick Trees (Binary Indexed Trees), and Disjoint Set Union (Union-Find).

This syllabus prepares you for success in technical interviews and real-world software challenges. Enroll now and take your first step towards a rewarding career in software development!