Data Structures and Algorithms in Python

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Glassbyte Team

11:39:50

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1. Introduction

1. Course objectives, structure and more.mp4

08:28

2. How computers work.mp4

12:47

3. What are algorithms.mp4

05:29

4. What are data structures.mp4

06:02

2. The Big O Notation

1. Intro.mp4

06:35

2. Constant O(1).mp4

03:28

3. Linear O(n).mp4

04:43

4. Quadratic O(n2).mp4

05:38

5. Logarithmic O(logn).mp4

10:16

6. Space Complexity.mp4

03:57

7. Asymptotic Complexity.mp4

09:45

3. Recursion

1. The Call Stack and function execution.mp4

09:53

2. What is Recursion.mp4

09:08

3. Potential Problems.mp4

08:35

4. Recursion vs Iteration.mp4

08:22

5. Big O of Recursive Functions.mp4

14:39

4. Arrays and Hash Tables

1. Arrays.mp4

06:57

2. Big O of Arrays.mp4

08:12

3. Hash Tables (Dictionaries).mp4

11:21

4. Big O of Hash Tables.mp4

04:06

5. Singly Linked Lists

1. Intro.mp4

07:22

2. Append.mp4

11:32

3. Prepend.mp4

05:04

4. Pop Left.mp4

09:39

5. Pop Right.mp4

09:45

6. Remove.mp4

10:09

7. Reverse.mp4

13:37

8. Recap.mp4

06:43

9. A note on the last video.html

6. Doubly Linked Lists

1. Intro.mp4

03:03

2. Append.mp4

05:07

3. Prepend.mp4

03:47

4. Pop Left.mp4

04:57

5. Pop Right.mp4

04:31

6. Remove.mp4

07:22

7. Recap.mp4

03:47

7. Stacks and Queues

1. Stacks - Intro.mp4

03:10

2. Stacks - Array Implementation.mp4

02:47

3. Stacks - Linked Lists Implementation.mp4

08:13

4. Stacks - Recap.mp4

05:01

5. Queues - Intro.mp4

04:04

6. Queues - Linked Lists Implementation.mp4

06:29

7. Queues - Deques.mp4

03:48

8. Binary Search Trees

1. Trees Intro.mp4

11:41

2. Binary Search Trees Intro.mp4

05:53

3. Insert.mp4

13:36

4. Contains.mp4

06:20

5. Remove Intro.mp4

06:49

6. Remove Node no children.mp4

06:37

7. Remove Node one child.mp4

05:59

8. Remove Node two children.mp4

12:44

9. Tree Traversal

1. Intro.mp4

03:08

2. Breadth First Traversal.mp4

14:13

3. DFT Pre Order Iterative.mp4

10:20

4. DFT Pre Order Recursive.mp4

14:07

5. DFT In Order Iterative.mp4

12:26

6. DFT In Order Recursive.mp4

07:41

7. DFT Post Order Iterative.mp4

11:21

8. DFT Post Order Recursive.mp4

06:51

9. Recap.mp4

03:52

10. Heaps

1. Intro.mp4

09:10

2. Insert.mp4

14:30

3. Remove Max.mp4

14:54

4. Heapify.mp4

10:45

11. Graphs

1. Intro.mp4

08:48

2. Adding Vertices and Edges.mp4

05:31

3. Removing Vertices and Edges.mp4

08:11

4. Breadth First Traversal.mp4

17:51

5. Depth First Traversal Iterative.mp4

07:45

6. Depth First Traversal Recursive.mp4

08:17

12. Sorting

1. Intro.mp4

05:18

2. Insertion Sort.mp4

13:54

3. Selection Sort.mp4

09:40

4. Bubble Sort.mp4

11:04

5. Shell Sort.mp4

13:22

6. Heap Sort.mp4

12:46

7. Merge Sort.mp4

27:40

8. Quick Sort.mp4

22:46

9. Radix Sort.mp4

24:05

13. Congratulations

1. Congratulations and thank you.mp4

01:37

Description

Visualize the inner workings of data structures and algorithms, line by line, through comprehensive animations

What You'll Learn?

Understand how computers store and work with data
Analyze the space and memory utilization of any algorithm using the Big O Notation
Dive deep into the mechanisms of function execution and demystify the concept of Recursion
Implement from scratch the most common 9 Data Structures
Understand how the best known 8 sorting algorithms work
Learn the searching / traversing algorithms for trees and graphs
Improve your problem solving skills
Learn the behind the scenes of the basic data structures (arrays and hash maps)
Understand common programming patterns
Learn everything you need to know for the technical interview

Who is this for?

Self-taught engineers with a career in a different field that want to switch to the tech industry

Anyone who is preparing for a technical interview

Engineers who want to build better tech fluency, land better roles, and push their career to new heights

Computer Science students who want to supplement their studies with alternative learning materials

What You Need to Know?

Basic coding concepts in any programming language

No previous data structures and algorithms knowledge needed

A computer to practice on (Windows, Mac or Linux)

More details

Description
Â Â Building reliable and highly performant software requires knowledge that goes beyond a certain programming language or framework. It requires a solid understanding of how data is organized in memory, how it can be manipulated, sorted or searched into. Thereâ€™s a reason why all the big tech companies such as Google, Amazon or Netflix focus their technical interviews on those topics. Whether you do mobile apps, websites, games, machine learning or any other work that involves coding, you need a good grasp of Data Structures and Algorithms.
Â Â Many self taught developers and aspiring engineers often feel they lack the knowledge when having to decide on the right data structure or the right approach for solving a problem. If you ever felt that way, this material is the right choice for you. This course packs months of Computer Science subject matter to get you on the same level of proficiency as someone with a Computer Science degree.

What sets us apart ?
Â Â Every video begins with an in depth analysis of the topic at hand. At this stage we wonâ€™t write any code yet, but rather learn how to approach the problem, think of ways we could solve it and build a mental model of the solution.
Â Â We then go on to code the algorithm step by step. But we donâ€™t stop there. We take one or more examples and walk through the code line by line. And we mean that literally. You will see how the code runs from top to bottom and how data flows and changes during execution. We find this method the absolute best way to really understand the inner workings of an algorithm.
Â Â Weâ€™ll also analyze the time performance and space utilization of every algorithm and method we write using the Big O Notation. Weâ€™ll talk about the strengths and weaknesses of each data structure and discuss their real world usage. Apart from all of that, youâ€™ll also learn things like recursion, how computers work under the hood, problem solving techniques, common programming patterns and much more.

What does this course cover ?
How computers work under the hood
What a data structure is
What an algorithm is
Problem solving techniques
Big O Notation - how to analyze the time performance and space utilization of algorithms. This is done for every single function/algorithm we write.
Gain a deeper understanding of how code works
Recursion

Data Structures:
Arrays
Hash Tables
Singly Linked Lists
Doubly Linked Lists
Stacks
Queues
Binary Search Trees
Tree Traversal
Heaps
Graphs

Sorting Algorithms:
Insertion Sort
Selection Sort
Bubble Sort
Shell Sort
Heap Sort
Merge Sort
Quick Sort
Radix Sort
Thanks for considering, and I hope this course will help you in your journey. Happy learning!
Who this course is for:
Self-taught engineers with a career in a different field that want to switch to the tech industry
Anyone who is preparing for a technical interview
Engineers who want to build better tech fluency, land better roles, and push their career to new heights
Computer Science students who want to supplement their studies with alternative learning materials

User Reviews

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The first steps into Computer Science can be daunting, and for good reasons. These topics are, truth be told, quite difficult. And while there are many books and courses out there that tackle them quite well, none really cover them like this. Glassbyte has a unique combination of beautifully animated videos and a line by line analysis of the code execution. I truly believe that through visual illustrations, one can get a deeper understanding of even the most technically complex subject. As a self-taught engineer, I experienced first hand the difficulty of learning data structures and algorithms from books or whiteboard style videos. Only after I started animating them and seeing how they run line by line, did I truly understand how they worked under the hood. Nowadays, after more than 7 years since my journey began, I am working as an engineer in the blockchain/crypto space, while my passion for learning and teaching through animations led me to start my Youtube channel on the side.I hope my courses will help you reach your goals. Happy learning!

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