Course

Placement Oriented Data Structures in Python

Technical rounds in an interview assess not only your coding skills but also your conceptual understanding

20 Per Batch Beginner 60 Hrs
Instructor Name - Dr. S.Lovelyn Rose

About this Course

This course is designed to start from the Python libraries/concepts needed for Data Structures and help you master the fundamental Data Structures, Algorithms and Design techniques with coding examples. The icing is to solve common interview questions from LeetCode and Striver

Skills you'll gain

Problem-Solving Skills Mastering Core Data Structures Efficient Coding Practices

Syllabus

  • Introduction to Data Structures
  • Primitive Data Types in Python

  • Lists (Dynamic Arrays in Python)
  • Tuples (Immutable Lists)
  • Sets and Arrays
  • Records, Structs & Data Transfer Objects
  • Dictionaries (Key-Value Pairs)

  • Linear Search, Binary Search (Iterative & Recursive), Interpolation Search
  • Interview Focus: Comparing search methods and handling edge cases

  • Insertion Sort - Code, best and worst case complexity
  • Selection Sort - Code, best and worst case complexity
  • Bubble Sort - Code, best and worst case complexity
  • Merge Sort - Recurrence trees, Python code, time and space complexity
  • Quick Sort - Recurrence trees, Python code, time and space complexity
  • Interview Focus - Choosing the right sorting algorithm based on constraints

  • Stack (LIFO)
  • Queue (FIFO)
  • Deque (Double Ended Queue)

  • Singly Linked Lists
  • Doubly Linked Lists
  • Circular Linked Lists

  • Stacks - Operations, infix to postfix conversion, evaluation
  • Queues - Circular queues, Deque operations

  • Introduction to Hashing - Concept, importance, and use cases
  • Hash Functions - Properties and designing efficient hash functions
  • Collision Handling - Chaining, Open Addressing techniques
  • Python’s Built-in Hash Tables - dict and set

  • Binary Trees
  • Binary Search Trees (BST)
  • Balanced Trees (AVL & Red Black Trees)
  • Heap (Priority Queue Implementation)

  • Graph Representation
  • Graph Traversal
  • Shortest Path Algorithms
  • Minimum Spanning Tree (MST) Algorithms

  • Tries (Prefix Trees)
  • Disjoint Set (Union-Find Algorithm)

  • LRU Cache Implementation (using functools.lru_cache)
  • Graph-Based Social Network Analysis
  • Auto Suggestions using Tries
  • Web Crawler using BFS & DFS
  • Shortest Path in Google Maps (Dijkstra’s Algorithm)
  • Job Scheduling using Heaps
  • Interview Focus: Integrating multiple data structures to solve real-world problems and system design basics

  • Dynamic Programming
  • Backtracking
  • Greedy Algorithms
  • Divide & Conquer / Recursion
  • Additional Interview Strategies

  • Basic String Manipulation and Pattern Matching
  • Two Pointer and Sliding Window Techniques for Strings
  • Core Problems
  • Divide & Conquer / Recursion
  • Interview Focus

About the Instructor

Dr .S.Lovelyn Rose

Founder and CEO

20 Students

15 Topics

Dr. S. Lovelyn Rose—a Doctorate in AI, seasoned academic with 22 years of experience teaching Python, Data Structures, Algorithms, and Design Techniques, and author of “Data Structures” by Wiley. With her extensive academic and industry background, she’ll guide you through fundamental DS concepts, ensuring you gain clarity and confidence in applying them to real-world problems.

Fee

₹ 34,999

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Duration

60 Hrs

Lectures

56

Enrolled

20 students

Language

English - Tamil

Skill Level

Beginner

Deadline

Life Time

Certificate

Yes

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