Master Data Structures and Algorithms in Python

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Ravi Singh

9:57:48

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1. Array problems solving techniques with examples

1.1 TimeComplexityProblems.mp4

14:37

1. Time Complexity and Space Complexity Introduction.mp4

12:24

2. Searching Algorithms Introduction & Implementation.mp4

06:29

3. Segregation logic to Sort an array of 0s, 1s and 2s.mp4

03:03

4. Merge Sort Implementation.mp4

23:04

5. Maximum Value in an array of Increasing and Decreasing using Binary Search.mp4

06:29

6. Digit rearrangement method to find next greater number with same set of digits.mp4

04:16

7. Greedy Techniques to find minimum number of platforms.mp4

05:37

8. Techniques to print matrix in spiral order without any extra space.mp4

12:24

9. Count frequencies of array elements in O(n) time complexity.mp4

18:04

10. Linear time approach to solve Stock Buy Sell Problem.mp4

05:43

11. Merge sort method to Count inversion in an array.mp4

08:53

12. Binary search method to find Median of two sorted Array.mp4

07:17

13. Minimum Window Substring.mp4

05:22

14. Search an element in a sorted and rotated array.mp4

04:35

15. Segregation logic to Sort an array of 0s, 1s and 2s (Assigment).mp4

05:09

16. Techniques to print matrix in spiral order without any extra space (Assignment).mp4

12:24

17. Count frequencies of array elements in O(n) time complexity (Assignment).mp4

07:41

18. Remove Duplicate From String (Assignment).mp4

03:57

2. Binary Tree

1. Binary Tree Traversal Implementation.mp4

06:41

2. Binary Tree to Doubly Linked List Conversion.mp4

09:06

3. Print all the boundary nodes of Binary Tree.mp4

08:22

4. Diameter of Binary tree.mp4

04:28

5. Print nodes at k distance from root.mp4

04:51

6. Find All Nodes Distance K in Binary Tree.mp4

09:44

7. Bottom View of Binary Tree.mp4

04:13

8. Construct Tree from PostOrder.mp4

06:59

9. Spiral Order of Binary Tree.mp4

11:11

10. Print Left View of Binary Tree.mp4

07:07

11. Binary Tree Reverse Level Order Traversal.mp4

04:10

12. Serialize and Deserialize Binary Tree.mp4

12:05

3. Linked List

1. Add Number to Linked List.mp4

08:12

2. Linked List Even and Odd List.mp4

05:12

3. Flattering of LinkedList.mp4

03:43

4. Linked List Palindrome.mp4

07:21

5. Merge Sort for Linked Lists.mp4

09:38

6. Rearrange Linked List.mp4

09:31

7. Reverse K Linked List.mp4

09:36

4. Heap SortHashing

1. MinMax Heap Implementation.mp4

09:12

2. Heapify operation implementation.mp4

06:50

3. Four Sum Problem.mp4

11:24

4. Median of running data streams problem.mp4

20:11

5. Group Anagrams Together.mp4

07:56

6. Design and implement LRU.mp4

21:11

5. Recursion & Backtracking Concept and Implementation with Multiple Example

1. Knight Walk Problem.mp4

13:29

2. N Queen Problem.mp4

10:46

3. Print all Permutations of a given String.mp4

12:12

4. Print all possible words from phone digits.mp4

09:14

5. Recursion & Backtracking Concept and Implementation with Multiple Example.mp4

10:17

6. Implement pow(x, n).mp4

01:13

7. Rat Maze Problem.mp4

17:41

8. Sudoku solving Problem - 2.mp4

10:14

6. Graph

1. Alien Dictionary.mp4

08:06

2. Cycle Graph.mp4

11:10

3. Package Dependency Problem Using Topological Sorting.mp4

16:02

4. Breadth first search algorithm to find Number of IsLand in matrix.mp4

10:52

5. Breadth first search algorithm to solve Rotten Orange Problem.mp4

14:02

6. Breadth first search algorithm to solve snake ladder problem.mp4

13:52

7. All Paths From Source to Target.mp4

14:26

8. Topological sorting concepts and implementation.mp4

11:44

9. Trie data Structure implementation.mp4

11:44

10. Trie data Structure implementation.mp4

14:22

Description

From Basic to Advanced Concepts, Practical Implementation and Problem Solving, Mastery of Data Structures and Algorithm

What You'll 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 is this for?

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.

What You Need to Know?

Basic Programming Knowledge

More details

Description
Apply Coupon code, get maximum discount: 7A4A79AA47D9D9F070B7
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, and then 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:
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.
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.
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.
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.
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.
Who this course is for:
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.

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As a Developer and Architect i worked in top product based companies like WalmartLabs, Amazon etc.I always have keen interest in logic development, algorithm and data Structure. I worked as tutor and teaches hundred of students to crack coding interviews. I have my youtube channel to teach students and give them tips to do preparation for interview.

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