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Data Structures and Algorithms: In Depth DSA using Java

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  • 609 Students
  • Updated 11/2025
4.4
(110 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
Syed Mohiuddin
Rating
4.4
(110 Ratings)
3 views

Course Overview

Data Structures and Algorithms: In Depth DSA using Java

Learn Java Data Structures, Algorithms (DSA) with Animated Examples, includes Dynamic Programming, Backtracking etc...

This course will help you in better understanding of the basics of Data Structures and how algorithms are implemented in Java. This course consists of Videos which covers the theory concepts + implementation in Java.


There’s tons of concepts and content in this course:

  • Basics of data structures & Algorithms

  • Analysis of Algorithms (Big O, Time and Space complexity)

  • Recursion & Analysis of Recursive Algorithms

  • Searching Algorithms

  • Sorting Algorithms

  • Linked List

  • Stacks

  • Queues

  • Binary Trees

  • Binary Search Trees

  • Balanced Binary Search Trees

  • Priority Queues and Heaps

  • Hashing

  • Graphs

  • Graph Traversal Algorithms

Followed by Advanced Topics of Algorithms:

  • Sets and Disjoint Sets

  • Divide and Conquer Approach - Introduction

  • Divide and Conquer - Binary Search

  • Divide and Conquer - Finding Maximum and Mininum

  • Divide and Conquer - Merge Sort

  • Divide and Conquer - Quick Sort

  • Divide and Conquer - Selection Algorithm

  • Divide and Conquer - Strassens Matrix Multiplication

  • Divide and Conquer - Closest Pair

  • Divide and Conquer - Convex Hull

  • Greedy Method - Introduction

  • Greedy Method - Knapsack Problem

  • Greedy Method - Job Sequencing with Deadlines

  • Greedy Method - Mininum Cost Spanning Tree (Prim's & Kruskal's Algorithms)

  • Greedy Method - Optimal Storage on Trees

  • Greedy Method - Optimal Merge Pattern

  • Greedy Method - Single Source Shortest Path (Dijkstra's Algorithm)

  • Dynamic Programming - Introduction

  • Dynamic Programming - Multistage Graphs

  • Dynamic Programming - All Pairs Shortest Path

  • Dynamic Programming - Single Source Shortest Path

  • Dynamic Programming - Optimal Binary Search Trees

  • Dynamic Programming - 0/1 Knapsack Problem

  • Dynamic Programming - Reliability Design

  • Dynamic Programming - Travelling Salespersons Problem

  • Backtracking - Introduction

  • Backtracking - n-Queesn Problem

  • Backtracking - Sum of Subsets Problem

  • Backtracking - Graph Coloring Problem

  • Backtracking - Hamiltonian Cycles Problem

  • Backtracking - 0/1 Knapsack Problem

  • Branch & Bound - Introduction

  • Branch & Bound - n-Queens Problem

  • Branch & Bound - Job Sequencing Problem

  • Branch & Bound - 0/1 Knapsack Problem


Again, each of these sections includes detailed videos tutorial.


Course Content

  • 10 section(s)
  • 398 lecture(s)
  • Section 1 Introduction
  • Section 2 Analysis of Algorithms
  • Section 3 Recursion
  • Section 4 Searching Algorithms
  • Section 5 Sorting Algorithms
  • Section 6 Linked List
  • Section 7 Circular Linked List
  • Section 8 Doubly Linked List
  • Section 9 Stacks
  • Section 10 Queues

What You’ll Learn

  • Understand Complexity of Algorithms ie Time and Space they take at runtime
  • Learn and compare Algorithms used in Searching and Sorting
  • Learn different Data Structures and how to use them in applications
  • Learn how to Code and Implement various data structures and algorithms in Java

Reviews

  • S
    Seray Kara
    2.0

    He is teaching good but sometimes it gets boring because he is talking like he is just reading. But still fine

  • s
    sushreesmita dhal
    4.0

    I have started and its easy to understand

  • M
    Mayank Tyagi
    5.0

    i loved it to be honest , i was not sure about taking this course....but now i am feeling quite confident and comfortable with this, THANKYOU SIR

  • S
    Sourav Sen
    3.5

    why logN

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