Data Structures for Absolute Beginners in Python

Data Structures for Absolute Beginners in Python, available at $19.99, has an average rating of 4.2, with 63 lectures, based on 13 reviews, and has 3022 subscribers.

You will learn about Understand the most important data structures Implement Data structures from scratch in python Analyze algorithms using the big O notation Reverse a linked list Understand and implement stacks, queues, trees, linked lists and graphs from scratch This course is ideal for individuals who are Beginner python programmers curious about data structures or Beginners wanting to up their programming game or Beginners interested in learning about data structures from scratch It is particularly useful for Beginner python programmers curious about data structures or Beginners wanting to up their programming game or Beginners interested in learning about data structures from scratch.

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Summary

Title: Data Structures for Absolute Beginners in Python

Price: $19.99

Average Rating: 4.2

Number of Lectures: 63

Number of Published Lectures: 63

Number of Curriculum Items: 63

Number of Published Curriculum Objects: 63

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Understand the most important data structures

Implement Data structures from scratch in python

Analyze algorithms using the big O notation

Reverse a linked list

Understand and implement stacks, queues, trees, linked lists and graphs from scratch

Who Should Attend

Beginner python programmers curious about data structures

Beginners wanting to up their programming game

Beginners interested in learning about data structures from scratch

Target Audiences

Beginner python programmers curious about data structures

Beginners wanting to up their programming game

Beginners interested in learning about data structures from scratch

You’ll learn about the most important and basic data structures that every veteran programmer knows about in detail. By the end of the course, you’ll be able to implement these from absolute scratch.

The course is designed to help the students write their own code. Each module has explanation parts and implementation parts, you’re encouraged to implement an explained topic on your own.

Data Structures covered in the course.

Singly Linked Lists

Doubly Linked Lists

Stacks

Queues

Binary Search Trees

Graphs

Computational Complexity

Algorithms

Reversing a linked list

Recursive and iterative tree traversal

Breadth First Search

Depth First Search

Analysis

Big O notation

Who is this course for?

Many people learn programming and are told to learn data structures and algorithms to pass coding interviews and get jobs. This course is designed for an individual who has some python programming knowledge and wants to get better at it by learning data structures. Even if you have no python experience but know some other programming language, this can be a great chance to learn python. For people who don’t know python, this provides programming problems to get better at python.

How the course is designed

The course is designed with 7 major modules. We go from installing python, to setting up jupyter notebook to understanding and implementing data structures from scratch. We also visualize computational complexity of different operations we write for these data structures in the final section on computational complexity.

What will you get out of it

Better understanding of data structures.

More tools at your disposal for solving programming problems.

Ability to implement data structures from scratch in python.

Opportunity to practice python.

Course Curriculum

Chapter 1: Introduction

Lecture 1: What this course is about

Lecture 2: How to take the course effectively

Chapter 2: Environment Setup

Lecture 1: Setting up your environment

Chapter 3: Stacks and Queues

Lecture 1: Section Introduction

Lecture 2: Stack

Lecture 3: Stack Implementation

Lecture 4: Valid Brackets Problem

Lecture 5: Valid Brackets Problem solution

Lecture 6: Queues

Lecture 7: Queue Implementation

Lecture 8: Section Conclusion

Chapter 4: Singly Linked Lists

Lecture 1: Section Introduction

Lecture 2: Introduction to Linked Lists

Lecture 3: Singly Linked List Implementation

Lecture 4: Singly Linked List: Push Method

Lecture 5: Singly Linked List: Unshift Method

Lecture 6: Singly Linked List: Shift Method

Lecture 7: Singly Linked List Traversal

Lecture 8: Singly Linked List Pop

Lecture 9: Singly Linked List Insert

Lecture 10: Singly Linked List Remove

Lecture 11: Singly Linked List Reverse

Lecture 12: Singly Linked Lists: Conclusion

Chapter 5: Doubly Linked Lists

Lecture 1: Section Introduction

Lecture 2: Doubly Linked Lists: Introduction

Lecture 3: Doubly Linked Lists: Implementation

Lecture 4: Doubly Linked Lists: Push Method

Lecture 5: Doubly Linked Lists: Unshift Method

Lecture 6: Doubly Linked Lists: Shift Method

Lecture 7: Doubly Linked Lists: Pop Method

Lecture 8: Doubly Linked Lists: Insert Method

Lecture 9: Doubly Linked Lists: Remove

Lecture 10: Doubly Linked Lists: Reverse

Lecture 11: Doubly Linked Lists: Conclusion

Chapter 6: Binary Search Trees

Lecture 1: Section Introduction

Lecture 2: Binary Search Trees: Introduction

Lecture 3: Binary Search Trees: Implementation

Lecture 4: Binary Search Trees: Insertion Introduction

Lecture 5: Binary Search Trees: Insertion Implementation (Iterative)

Lecture 6: Binary Search Trees: Insertion Implementation (Recursive)

Lecture 7: Binary Search Trees: Preorder Traversal (Part 1)

Lecture 8: Binary Search Trees: Preorder Traversal Part 2

Lecture 9: Binary Search Trees: Inorder Traversal

Lecture 10: Binary Search Trees: Postorder Traversal

Lecture 11: Binary Search Trees: Delete Explanation

Lecture 12: Binary Search Trees: Delete Implementation

Lecture 13: Binary Search Trees: Search

Lecture 14: Binary Search Trees: Conclusion

Chapter 7: Graphs

Lecture 1: Section Introduction

Lecture 2: Graphs: The Basics

Lecture 3: Graphs: Implementation

Lecture 4: Graphs: Breadth First Search

Lecture 5: Graphs: Depth First Search

Lecture 6: Graphs: Conclusion

Chapter 8: Computational Complexity

Lecture 1: Section Introduction

Lecture 2: Big O Notation: Introduction

Lecture 3: Big O: Arrays

Lecture 4: Big O: Stacks and Queues

Lecture 5: Big O: Linked Lists

Lecture 6: Big O: Binary Search Trees

Lecture 7: Big O: Graphs

Lecture 8: Big O: Conclusion

Chapter 9: Course Conclusion

Lecture 1: Course Conclusion and whats next

Instructors

Abdul Rauf
Engineer

Rating Distribution

1 stars: 0 votes

2 stars: 1 votes

3 stars: 1 votes

4 stars: 7 votes

5 stars: 4 votes

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