Data Structures and Algorithms Complete Course

Data Structures and Algorithms – Complete Course, available at $54.99, has an average rating of 3.5, with 67 lectures, based on 44 reviews, and has 209 subscribers.

You will learn about Data Structures Algorithms and Analysis of Algorithms Programming interview skills This course is ideal for individuals who are Software Engineers or Computer Science students or Data Scientists It is particularly useful for Software Engineers or Computer Science students or Data Scientists.

Enroll now: Data Structures and Algorithms – Complete Course

Summary

Title: Data Structures and Algorithms – Complete Course

Price: $54.99

Average Rating: 3.5

Number of Lectures: 67

Number of Published Lectures: 67

Number of Curriculum Items: 71

Number of Published Curriculum Objects: 71

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Data Structures

Algorithms and Analysis of Algorithms

Programming interview skills

Who Should Attend

Software Engineers

Computer Science students

Data Scientists

Target Audiences

Software Engineers

Computer Science students

Data Scientists

In this course we will understand different data structures and how to use them effectively for solving problems. It is expected that the students have basic experience in any high-level programming language. Data structures and algorithms are a crucial part of programming interviews. This course is a complete course on Complete data structure and algorithms. The main focus here will be mastering the Data structures, implementing those and some problems explaining application of those data structures and understand different programming paradigms, analysis of algorithms and applying different data structures.
In this course, we will cover the following topics:

Time and Space complexity of algorithms

Arrays,

Linked Lists,

Trees – Representation, binary trees, binary search trees, balanced binary search trees, and related problems

Stacks and Queues,

Heaps,

Graphs – representation, traversal of graph using breadth-first search, depth first search, graph algorithms

Hash Table,

Tries

Recursion

Dynamic Programming

A good understanding of data structures and algorithms is very crucial for programming interview. After completing this course you should be able to understand which data structures and algorithms should be used to solve a problem and why. It will not only prepare you for your coding interviews, but also make you a better programmer in general.

So, let’s start our wonderful journey towards mastering data structures and algorithms.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Overview

Lecture 2: What are data structures and algorithms?

Chapter 2: Analysis of Algorithms

Lecture 1: Analysis of Algorithms – Running Time

Lecture 2: Asymptotic Analysis of Algorithms

Lecture 3: Big O notation

Lecture 4: Big Omega notation

Lecture 5: Big Theta Notation

Chapter 3: Arrays

Lecture 1: Arrays – Introduction

Lecture 2: Arrays in C++, Java, Python

Lecture 3: Exercise: Build Array from Permutation

Lecture 4: Exercise: Concatenation of Array

Lecture 5: Running Sum of 1d Array

Lecture 6: Dynamic Arrays – Introduction

Lecture 7: 2D Arrays

Chapter 4: Linked Lists

Lecture 1: Linked List – Introduction

Lecture 2: Linked List – Advantages and Disadvantages

Lecture 3: Linked List – Representation and Traversal

Lecture 4: Linked List – Insertion cases and Code

Lecture 5: Linked List – Deletion

Lecture 6: Linked List – Search a key

Lecture 7: Find Kth Node from end of a Linked List

Lecture 8: Find Middle of a Linked List

Lecture 9: Detect Loop in Linked List

Lecture 10: Why Floyds Cycle detection works?

Lecture 11: Find the beginning of Loop in Linked List

Chapter 5: Trees

Lecture 1: Trees – Introduction

Lecture 2: Binary Trees – Representation

Lecture 3: Simple Binary Tree in C++

Lecture 4: Properties of Binary Tree

Lecture 5: Types of Binary Tree

Lecture 6: Insertion in Binary Tree – Level Order Insertion

Lecture 7: Deletion in Binary Tree – in single traversal

Lecture 8: Tree Traversals – Inorder, Preorder, Postorder, Level Order

Lecture 9: Range sum of a Binary Search Tree

Lecture 10: Path Sum of Binary Tree

Lecture 11: Exercise – Two Sum in Binary Search Tree

Chapter 6: Stacks and Queues

Lecture 1: Stack data strcuture

Lecture 2: Queue data structure

Lecture 3: Stacks – C++ STL

Lecture 4: Queue – C++ STL

Lecture 5: Inorder traversal of Binary Tree without recursion

Chapter 7: Graphs

Lecture 1: Graphs – Introduction

Lecture 2: Graph Representation

Lecture 3: Breadth First Search – Graph Traversal

Lecture 4: Depth First Search – Graph Traversal

Lecture 5: Applications of DFS and BFS

Lecture 6: Iterative DFS

Lecture 7: Pre and Post visited times in DFS

Lecture 8: DFS – Types of Edges

Lecture 9: Cycle Detection in Directed Graph

Lecture 10: Cycle Detection in Undirected Graph

Lecture 11: Disjoint Set (Union-Find) Algorithm – Introduction

Chapter 8: Heaps

Lecture 1: Binary Heap – Introduction

Lecture 2: Binary Heap – Representation

Lecture 3: Binary Heap Implementation

Lecture 4: Build Heap and its Time Complexity

Lecture 5: Merge k sorted linked lists

Chapter 9: Hash Table

Lecture 1: Hash Table – Introduction

Lecture 2: Hash Table – Principle

Lecture 3: Designing a Hash Table

Lecture 4: Design a Hash Set – Explanation and solution

Lecture 5: Design a Hash Map

Lecture 6: Using Hash Set in C++, Java and Python

Lecture 7: Complexity Analysis of Hash Tables

Chapter 10: Recursion

Lecture 1: Mastering Recursion for Programming Interviews

Lecture 2: Sum of left leaves of Binary Tree

Chapter 11: Conclusion

Lecture 1: Conclusion and Thank you

Instructors

Abhishek Kumar
Computer Scientist at Adobe

Rating Distribution

1 stars: 2 votes

2 stars: 6 votes

3 stars: 6 votes

4 stars: 10 votes

5 stars: 20 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!