Course Content
Subtitle Guide – Hướng dẫn thêm phụ đề
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01 – Introduction
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001 How To Succeed In This Course
05:04
002 Join Our Online Classroom!
04:01
003 Exercise Meet Your Classmates and Instructor
004 Monthly Coding Challenges, Free Resources and Guides
02 – Getting More Interviews
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001 Section Overview
05:39
002 Resume
05:09
003 Exercise Resume Walkthrough
17:05
004 Resume Review
02:37
005 Resources Resume Templates
006 What If I Don’t Have Enough Experience
15:03
007 Optional Exercise Github Master
008 LinkedIn
08:22
009 Optional Exercise LinkedIn Endorsements
010 Portfolio
03:23
011 Resources Free Portfolio Templates
012 Email
08:24
013 Resources Email
014 Where To Find Jobs
06:02
015 Resources Where To Find Jobs
016 When Should You Start Applying
03:34
017 Section Summary
02:17
03 – Big O
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001 Setting Up Your Environment
02:53
002 Section Overview
02:24
003 Python, Java, CC++, C#, Golang, Swift, Kotlin, TypeScript, + Perl Solutions!
004 Big O Cheatsheet
005 What Is Good Code
06:57
006 Big O and Scalability
11:08
007 O(n)
05:39
008 O(1)
06:10
009 Exercise Big O Calculation
010 Solution Big O Calculation
05:54
011 Exercise Big O Calculation 2
012 Solution Big O Calculation 2
02:29
013 Simplifying Big O
01:50
014 Big O Rule 1
04:28
015 Big O Rule 2
06:37
016 Big O Rule 3
03:13
017 O(n^2)
07:13
018 Big O Rule 4
06:47
019 Big O Cheat Sheet
03:19
020 What Does This All Mean
05:32
021 O(n!)
01:18
022 3 Pillars Of Programming
03:32
023 Space Complexity
02:22
024 Exercise Space Complexity
06:24
025 Exercise Twitter
07:13
026 Optional Javascript Loops
03:27
027 Section Summary
04:43
04 – How To Solve Coding Problems
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001 Section Overview
05:04
002 What Are Companies Looking For
03:05
003 What We Need For Coding Interviews
03:27
004 Exercise Google Interview
02:31
005 Exercise Interview Question
20:33
006 Exercise Interview Question 2
22:59
007 Review Google Interview
01:30
008 Optional Exercise Google Interview On Your Own
009 Section Summary
03:36
05 – Data Structures Introduction
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001 Section Overview
01:58
002 What Is A Data Structure
05:53
003 How Computers Store Data
12:34
004 Data Structures In Different Languages
03:28
005 Operations On Data Structures
03:05
06 – Data Structures Arrays
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001 Arrays Introduction
13:51
002 Static vs Dynamic Arrays
06:40
003 Quick Note Upcoming Video
004 Optional Classes In Javascript
24:52
005 Implementing An Array
17:19
006 Strings and Arrays
01:04
007 Exercise Reverse A String
01:35
008 Solution Reverse A String
10:31
009 Exercise Merge Sorted Arrays
00:44
010 Solution Merge Sorted Arrays
14:12
011 Interview Questions Arrays
012 Arrays Review
03:28
07 – Data Structures Hash Tables
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001 Hash Tables Introduction
04:10
002 Hash Function
05:56
003 Hash Collisions
09:43
004 Hash Tables In Different Languages
03:30
005 Exercise Implement A Hash Table
03:51
006 Solution Implement A Hash Table
17:25
007 keys()
06:11
008 Extra keys() Without Collision
009 Hash Tables VS Arrays
02:01
010 Exercise First Recurring Character
01:18
011 Solution First Recurring Character
16:11
012 Interesting Tidbit Python Dictionaries
013 Hash Tables Review
06:09
08 – Data Structures Linked Lists
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001 Linked Lists Introduction
02:26
002 What Is A Linked List
04:36
003 Exercise Imposter Syndrome
02:56
004 Exercise Why Linked Lists
02:05
005 Solution Why Linked Lists
05:35
006 What Is A Pointer
05:45
007 Our First Linked List
08:38
008 Solution append()
05:25
009 Solution prepend()
02:28
010 Node Class
02:42
011 insert()
05:12
012 Quick Note Upcoming Video
013 Solution insert()
13:08
014 Solution remove()
05:21
015 Doubly Linked Lists
03:18
016 Exercise Doubly Linked Lists
017 Solution Doubly Linked Lists
08:50
018 Singly VS Doubly Linked Lists
02:40
019 Exercise reverse()
01:30
020 Solution reverse()
07:38
021 Linked Lists Review
05:08
09 – Data Structures Stacks + Queues
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001 Stacks + Queues Introduction
02:58
002 Stacks
03:28
003 Queues
03:30
004 Exercise Stacks VS Queues
03:06
005 Solution Stacks VS Queues
03:39
006 Quick Note Upcoming Video
007 Optional How Javascript Works
24:12
008 Exercise Stack Implementation (Linked Lists)
02:23
009 Solution Stack Implementation (Linked Lists)
08:58
010 Exercise Stack Implementation (Array)
00:53
011 Solution Stack Implementation (Array)
03:56
012 Exercise Queue Implementation
01:48
013 Solution Queue Implementation
07:50
014 Queues Using Stacks
02:05
015 Stacks + Queues Review
02:19
10 – Data Structures Trees
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001 Trees Introduction
06:23
002 Binary Trees
05:45
003 O(log n)
07:00
004 Binary Search Trees
06:12
005 Balanced VS Unbalanced BST
03:42
006 BST Pros and Cons
02:26
007 Exercise Binary Search Tree
03:57
008 Solution insert()
10:10
009 Solution lookup()
04:54
010 Extra Exercise remove()
02:28
011 Solution remove()
07:41
012 AVL Trees + Red Black Trees
02:56
013 Resources AVL Trees + Red Black Trees
014 Binary Heaps
05:36
015 Quick Note on Heaps
01:08
016 Priority Queue
05:27
017 Trie
03:16
018 Tree Review
00:51
11 – Data Structures Graphs
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001 Graphs Introduction
02:28
002 Types Of Graphs
03:32
003 Exercise Guess The Graph
02:45
004 Graph Data
05:58
005 Exercise Graph Implementation
04:06
006 Solution Graph Implementation
04:51
007 Graphs Review
02:04
008 Data Structures Review
01:52
009 What Else Is Coming Up
01:53
12 – Algorithms Recursion
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001 Introduction to Algorithms
03:52
002 Recursion Introduction
05:36
003 Stack Overflow
06:17
004 Anatomy Of Recursion
10:27
005 Exercise Factorial
03:25
006 Solution Factorial
06:20
007 Exercise Fibonacci
01:59
008 Solution Fibonacci
11:21
009 Recursive VS Iterative
04:16
010 When To Use Recursion
04:00
011 Exercise Reverse String With Recursion
012 Recursion Review
02:47
13 – Algorithms Sorting
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001 Sorting Introduction
07:01
002 The Issue With sort()
06:51
003 Sorting Algorithms
03:38
004 Bubble Sort
03:46
005 Exercise Bubble Sort
006 Solution Bubble Sort
05:06
007 Selection Sort
02:39
008 Exercise Selection Sort
009 Solution Selection Sort
02:23
010 Dancing Algorithms
01:36
011 Insertion Sort
02:38
012 Exercise Insertion Sort
013 Solution Insertion Sort
02:06
014 Merge Sort and O(n log n)
08:59
015 Exercise Merge Sort
016 Solution Merge Sort
04:44
017 Stable VS Unstable Algorithms
018 Quick Sort
07:40
019 Optional Exercise Quick Sort
020 Which Sort Is Best
04:40
021 Resources Heap Sort
022 Radix Sort + Counting Sort
04:17
023 Resources Radix Sort + Counting Sort
024 Exercise Sorting Interview
01:27
025 Solution Sorting Interview
07:07
026 Sorting In Your Language
01:27
027 Sorting Review
02:53
14 – Algorithms Searching + BFS + DFS
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001 Searching + Traversal Introduction
01:34
002 Linear Search
03:37
003 Binary Search
06:05
004 Graph + Tree Traversals
03:56
005 BFS Introduction
02:45
006 DFS Introduction
03:23
007 BFS vs DFS
03:20
008 Resources BFS vs DFS
009 Exercise BFS vs DFS
00:44
010 Solution BFS vs DFS
03:16
011 breadthFirstSearch()
09:15
012 breadthFirstSearchRecursive()
05:33
013 PreOrder, InOrder, PostOrder
05:21
014 depthFirstSearch()
12:03
015 Optional Exercise Validate A BST
016 Graph Traversals
03:53
017 BFS in Graphs
02:07
018 DFS in Graphs
02:50
019 Dijkstra + Bellman-Ford Algorithms
05:11
020 Searching + Traversal Review
04:21
15 – Algorithms Dynamic Programming
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001 Dynamic Programming Introduction
01:51
002 Memoization 1
07:47
003 Memoization 2
03:56
004 Fibonacci and Dynamic Programming
05:33
005 Dynamic Programming
05:47
006 Implementing Dynamic Programming
09:12
007 Interview Questions Dynamic Programming
008 Dynamic Programming Review
04:45
16 – Non Technical Interviews
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001 Section Overview
02:38
002 During The Interview
09:04
003 Exercise Hero Stories
004 Tell Me About Yourself
05:30
005 Exercise Your Pitch
006 Why Us
05:06
007 Tell Me About A Problem You Have Solved
05:18
008 Exercise Past Projects
00:00
009 What Is Your Biggest Weakness
02:19
010 Exercise Your Biggest Weakness
011 Any Questions For Us
03:24
012 Resources Questions To Ask A Company
013 Secret Weapon
08:11
014 After The Interview
05:24
015 Section Summary
03:56
17 – Offer + Negotiation
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001 Section Overview
02:10
002 Handling Rejection
04:07
003 Negotiation 101
09:40
004 Handling An Offer
09:03
005 Handling Multiple Offers
07:29
006 Getting A Raise
07:41
007 Exercise Negotiation Master
008 Section Summary
02:09
18 – Thank You
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002 Thank You
00:52
19 – Extras Google, Amazon, Facebook Interview Questions
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001 Coding Problems
01:25
002 Top Interview Questions
003 Amazon Interview Questions
004 Facebook Interview Questions
00:00
005 Google Interview Questions
006 Domain Specific Questions
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20 – Extra Bits
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001 Learning Guideline
002 Quick Note Upcoming Videos
003 From JTS Learn to Learn
01:59
004 From JTS Start With Why
02:43
005 Coding Challenges
006 How To Use Leetcode
02:27
Master the Coding Interview: Data Structures + Algorithms
About Lesson

In the previous video, I mentioned the idea of Stable Algorithm, and how Merge Sort is a stable sort. What does that mean? Have a read through this stack overflow answer which is excellent. Sometimes, stable is a desired property when sorting:

https://stackoverflow.com/questions/1517793/what-is-stability-in-sorting-algorithms-and-why-is-it-important

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