Data Structure With C and Python

Master Data Structures with C & Python – Enrollment Open!

Unlock the power of efficient programming by mastering linear and non-linear data structures using real-world examples. By the end of this course, you will be able to implement arrays, linked lists, stacks, queues, trees, graphs, and more in C and Python, write clean, optimized code, and solve complex problems like a pro.

???? What You’ll Learn:

  • Core concepts of linear and non-linear data structures
  • Real-world applications: student marks, temperature tracking, product lists, and more
  • Side-by-side implementations in C and Python
  • Hands-on practice with menu-driven programs
  • Identify and fix common coding mistakes and improve code quality
  • Boost problem-solving skills for exams, interviews, and projects

???? Join the batch of this intensive training program! Limited seats available. ????

Course Details:

  • Seats: 20
  • Registration Deadline: Wednesday, Oct 29, 2025
  • Program Starts: Friday, Nov 03, 2025
  • Regular Fee: 10,000 BDT
  • Special Offer Fee: 8000 BDT
  • Schedule: Saturday, Monday and Thursday, 7:00 PM – 9:00 PM
  • Duration: 2 months
  • Mode: Live online sessions via Google Meet
  • Resources: Session recordings and study materials provided
  • Prerequisite: Basic knowledge of any programming language

???? Don’t miss this chance to elevate your programming skills and problem-solving abilities. Enroll Today!

This is a comprehensive course outline for a full-length Data Structures course suitable for university-level delivery. It covers both linear and non-linear data structures, including foundational theory, implementation (C/Python), complexity analysis, and real-world applications.

Module 0: Course Introduction & Setup

  • What are Data Structures & Why Are They Important?
  • Time and Space Complexity Recap (Big-O, Ω, Θ)
  • Static vs Dynamic Data Structures
  • Abstract Data Types (ADT)
  • Development Environment Setup (C /Python)

Module 1: Linear Data Structures

1.1 Arrays

  • Static vs Dynamic Arrays
  • Multi-dimensional Arrays
  • Array Operations: Insertion, Deletion, Searching
  • Applications (Prefix Sum, Sliding Window, etc.)

1.2 Strings

  • String Manipulations
  • Pattern Matching Algorithms (Naive, KMP, Rabin-Karp, etc.)

1.3 Linked Lists

  • Singly Linked List
  • Doubly Linked List
  • Circular Linked List
  • Skip Lists (Optional Advanced)
  • Applications (Hashing, Memory Management)

1.4 Stacks

  • Stack ADT
  • Stack Implementation (Array / Linked List)
  • Applications: Expression Evaluation, Recursion

1.5 Queues

  • Linear Queue
  • Circular Queue
  • Double Ended Queue (Deque)
  • Priority Queue

Module 2: Non-Linear Data Structures

2.1 Trees

  • Binary Trees (BT) – Traversals (Inorder, Preorder, Postorder, Level Order)
  • Binary Search Trees (BST)
  • AVL Trees (Rotations, Balancing)
  • Red-Black Trees (Optional Advanced)
  • B-Trees / B+ Trees (Used in Databases)
  • Segment Trees & Fenwick Tree (Binary Indexed Tree)

2.2 Heaps

  • Min Heap & Max Heap
  • Heapify Algorithm
  • Priority Queue using Heaps
  • Heap Sort

2.3 Hashing

  • Hash Functions
  • Collision Handling (Chaining, Open Addressing)
  • Dictionary / Map / Unordered Map Implementation

Module 3: Graph Data Structures

  • Graph Representation (Adjacency List / Matrix)
  • Directed vs Undirected Graph
  • Weighted vs Unweighted Graph
  • Traversal Algorithms:
    • BFS (Breadth-First Search)
    • DFS (Depth-First Search)
  • Shortest Path Algorithms:
    • Dijkstra’s Algorithm
    • Bellman-Ford Algorithm
    • Floyd-Warshall Algorithm
  • Minimum Spanning Tree:
    • Prim’s Algorithm
    • Kruskal’s Algorithm
  • Topological Sorting
  • Disjoint Set (Union-Find)

Module 4: Advanced & Specialized Data Structures

  • Tries (Prefix Tree)
  • Suffix Tree / Suffix Array (Optional Advanced)
  • LRU Cache (Using Linked List + HashMap)
  • Bloom Filters (For Probabilistic Queries)
  • K-D Trees & Quad Trees (For Spatial Data)

Module 5: Real-world Applications of Data Structures

  • Compiler Parsing (Stack & Tree Usage)
  • Social Network Friend Recommendation (Graph DS)
  • Database Indexing (B-Trees & Hashing)
  • Priority Schedulers (Heap)
    • Autocomplete Search (Trie)
  • File Systems (Tree + Hash)

Module 6: Final Project & Interview Preparation

  • Implement a Mini Search Engine / Dictionary / File System
  • 50+ Data Structure Interview Problems
  • Complexity Tradeoff Analysis

Register Here , for free demo class.

If you wish to do the course please make the payment to Bkash(Send Money): 01746539987
Once you’ve made the payment, kindly send a screenshot or the transaction details to WhatsApp: 01746539987

Instructor: Sukanta Paul

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