Master Data Structures and Algorithms in Python

Master Data Structures and Algorithms in Python, available at $22.99, has an average rating of 4.55, with 62 lectures, based on 16 reviews, and has 56 subscribers.

You will learn about Advance Data Structure and Algorithms in Python : arrays, linked lists, stacks, queues, trees, and graphs Building a strong foundation in computer science fundamentals for efficient problem-solving Analyzing time and space complexity of algorithms for efficiency Algorithm design techniques: divide and conquer, dynamic programming, and greedy algorithms Using algorithmic paradigms such as brute force, backtracking, and heuristics to solve problems efficiently. This course is ideal for individuals who are Essential for computer science candidate to gain in-depth knowledge about data structures and algorithms or Useful for software developers to improve skills in data storage, retrieval, and processing or Beneficial for IT professionals to learn new skills or update their knowledge about data structures and algorithms or Suitable for anyone with an interest in computer science and problem-solving or Intended for individuals who want to develop a strong foundation in computer science fundamentals. It is particularly useful for Essential for computer science candidate to gain in-depth knowledge about data structures and algorithms or Useful for software developers to improve skills in data storage, retrieval, and processing or Beneficial for IT professionals to learn new skills or update their knowledge about data structures and algorithms or Suitable for anyone with an interest in computer science and problem-solving or Intended for individuals who want to develop a strong foundation in computer science fundamentals.

Enroll now: Master Data Structures and Algorithms in Python

Summary

Title: Master Data Structures and Algorithms in Python

Price: $22.99

Average Rating: 4.55

Number of Lectures: 62

Number of Published Lectures: 62

Number of Curriculum Items: 62

Number of Published Curriculum Objects: 62

Original Price: ?999

Quality Status: approved

Status: Live

What You Will Learn

Advance Data Structure and Algorithms in Python : arrays, linked lists, stacks, queues, trees, and graphs

Building a strong foundation in computer science fundamentals for efficient problem-solving

Analyzing time and space complexity of algorithms for efficiency

Algorithm design techniques: divide and conquer, dynamic programming, and greedy algorithms

Using algorithmic paradigms such as brute force, backtracking, and heuristics to solve problems efficiently.

Who Should Attend

Essential for computer science candidate to gain in-depth knowledge about data structures and algorithms

Useful for software developers to improve skills in data storage, retrieval, and processing

Beneficial for IT professionals to learn new skills or update their knowledge about data structures and algorithms

Suitable for anyone with an interest in computer science and problem-solving

Intended for individuals who want to develop a strong foundation in computer science fundamentals.

Target Audiences

Essential for computer science candidate to gain in-depth knowledge about data structures and algorithms

Useful for software developers to improve skills in data storage, retrieval, and processing

Beneficial for IT professionals to learn new skills or update their knowledge about data structures and algorithms

Suitable for anyone with an interest in computer science and problem-solving

Intended for individuals who want to develop a strong foundation in computer science fundamentals.

Python is a powerful and versatile programming language, known for its simplicity and readability. This course will cover the fundamental concepts and techniques for organizing, storing, and manipulating data efficiently using Python.

The course will start with an introduction to basic data structures such as arrays, linked lists, stacks, and queues, andthen move on to more complex data structures such as trees and graphs.We will explore how to implement these data structures in Python, as well as how to use them to solve real-world problems.

The course will also cover various algorithms such as sorting, searching, and graph traversal, and we will analyze the time and space complexity of these algorithms to determine their efficiency. We will explore algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms, and we will apply these techniques to solve real-world problems.

In addition to the core data structures and algorithms, we will also cover topics such as data abstraction, complexity theory, and algorithmic paradigms such as brute force, backtracking, and heuristics.We will explore how to choose the appropriate paradigm for a given problem and how to use it to solve problems efficiently.

How data structure and algorithm course help to get placed in top tech companies?

A strong foundation in data structures and algorithms is essential for success in top tech companies, as they form the building blocks for software development. Here are some ways in which a data structure and algorithm course can help individuals get placed in top tech companies:

1. Problem-Solving Skills: Data structure and algorithm courses teach problem-solving skills that are essential for success in top tech companies. They provide a framework for approaching complex problems and breaking them down into smaller, more manageable tasks.

2. Efficiency: Top tech companies are always looking for ways to improve the efficiency of their software. Knowledge of data structures and algorithms helps individuals develop efficient programs that can handle large amounts of data quickly and reliably.

3. Competitive Edge:Many top tech companies look for candidates who have a strong foundation in computer science fundamentals. A data structure and algorithm course can provide individuals with a competitive edge when applying for jobs at these companies.

4. Technical Interviews: Technical interviews at top tech companies often focus on data structures and algorithms. A data structure and algorithm course can help individuals prepare for these interviews by giving them the necessary knowledge and practice to succeed.

5. Industry-Relevant Skills:A data structure and algorithm course can provide individuals with industry-relevant skills that are in high demand in top tech companies. These skills can be leveraged to stand out from other candidates and secure a position at a top tech company.

Overall, a data structure and algorithm course can help individuals develop the skills and knowledge necessary to succeed in top tech companies. It provides a strong foundation in computer science fundamentals and teaches problem-solving skills that are essential for success in the industry.

Course Curriculum

Chapter 1: Array problems solving techniques with examples

Lecture 1: Time Complexity and Space Complexity Introduction

Lecture 2: Searching Algorithms Introduction & Implementation

Lecture 3: Segregation logic to Sort an array of 0s, 1s and 2s

Lecture 4: Merge Sort Implementation

Lecture 5: Maximum Value in an array of Increasing and Decreasing using Binary Search

Lecture 6: Digit rearrangement method to find next greater number with same set of digits

Lecture 7: Greedy Techniques to find minimum number of platforms

Lecture 8: Techniques to print matrix in spiral order without any extra space

Lecture 9: Count frequencies of array elements in O(n) time complexity

Lecture 10: Linear time approach to solve Stock Buy Sell Problem

Lecture 11: Merge sort method to Count inversion in an array

Lecture 12: Binary search method to find Median of two sorted Array

Lecture 13: Minimum Window Substring

Lecture 14: Search an element in a sorted and rotated array

Lecture 15: Segregation logic to Sort an array of 0s, 1s and 2s (Assigment)

Lecture 16: Techniques to print matrix in spiral order without any extra space (Assignment)

Lecture 17: Count frequencies of array elements in O(n) time complexity (Assignment)

Lecture 18: Remove Duplicate From String (Assignment)

Chapter 2: Binary Tree

Lecture 1: Binary Tree Traversal Implementation

Lecture 2: Binary Tree to Doubly Linked List Conversion

Lecture 3: Print all the boundary nodes of Binary Tree

Lecture 4: Diameter of Binary tree

Lecture 5: Print nodes at k distance from root

Lecture 6: Find All Nodes Distance K in Binary Tree

Lecture 7: Bottom View of Binary Tree

Lecture 8: Construct Tree from PostOrder

Lecture 9: Spiral Order of Binary Tree

Lecture 10: Print Left View of Binary Tree

Lecture 11: Binary Tree Reverse Level Order Traversal

Lecture 12: Serialize and Deserialize Binary Tree

Chapter 3: Linked List

Lecture 1: Add Number to Linked List

Lecture 2: Linked List Even and Odd List

Lecture 3: Flattering of LinkedList

Lecture 4: Linked List Palindrome

Lecture 5: Merge Sort for Linked Lists

Lecture 6: Rearrange Linked List

Lecture 7: Reverse K Linked List

Chapter 4: Heap Sort/Hashing

Lecture 1: Min/Max Heap Implementation

Lecture 2: Heapify operation implementation

Lecture 3: Four Sum Problem

Lecture 4: Median of running data streams problem

Lecture 5: Group Anagrams Together

Lecture 6: Design and implement LRU

Chapter 5: Recursion & Backtracking Concept and Implementation with Multiple Example

Lecture 1: Knight Walk Problem

Lecture 2: N Queen Problem

Lecture 3: Print all Permutations of a given String

Lecture 4: Print all possible words from phone digits

Lecture 5: Recursion & Backtracking Concept and Implementation with Multiple Example

Lecture 6: Implement pow(x, n)

Lecture 7: Rat Maze Problem

Lecture 8: Sudoku solving Problem – 2

Chapter 6: Graph

Lecture 1: Alien Dictionary

Lecture 2: Cycle Graph

Lecture 3: Package Dependency Problem Using Topological Sorting

Lecture 4: Breadth first search algorithm to find Number of IsLand in matrix

Lecture 5: Breadth first search algorithm to solve Rotten Orange Problem

Lecture 6: Breadth first search algorithm to solve snake ladder problem

Lecture 7: All Paths From Source to Target

Lecture 8: Topological sorting concepts and implementation

Lecture 9: Trie data Structure implementation

Lecture 10: Trie data Structure implementation

Chapter 7: BONUS SECTION

Lecture 1: Learn More and Crack top product based companies interview (BONUS LECTURE)

Instructors

Ravi Singh
Engineer at WalmartLabs

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5 stars: 14 votes

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