Course Curriculum
Introduction
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Getting More Interviews
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- Section Overview (5:39)
- Resume (5:09)
- Exercise: Resume Walkthrough (17:05)
- Resume Review (2:37)
- Resources: Resume Templates
- What If I Don't Have Enough Experience? (15:03)
- Optional Exercise: Github Master
- Optional Exercise: Github README
- LinkedIn (8:22)
- Optional Exercise: LinkedIn Endorsements
- Portfolio (3:23)
- Resources: Free Portfolio Templates
- Email (8:24)
- Resources: Email
- Where To Find Jobs? (6:02)
- Resources: Where To Find Jobs?
- When Should You Start Applying? (3:34)
- Section Summary (2:17)
- Monthly Industry Updates
Big O
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- Python, Java, C/C++, C#, Go, Swift, Kotlin, TypeScript, Scala, Rust, Perl, PHP
- Setting Up Your Environment (2:53)
- Section Overview (2:24)
- IMPORTANT: Replit Code
- What Is Good Code? (6:57)
- Big O and Scalability (11:08)
- O(n) (5:39)
- O(1) (6:10)
- Exercise: Big O Calculation
- Solution: Big O Calculation (5:54)
- Exercise: Big O Calculation 2
- Solution: Big O Calculation 2 (2:29)
- Simplifying Big O (1:50)
- Big O Rule 1 (4:28)
- Big O Rule 2 (6:36)
- Big O Rule 3 (3:13)
- O(n^2) (7:13)
- Big O Rule 4 (6:47)
- Big O Cheat Sheet (3:18)
- What Does This All Mean? (5:32)
- O(n!) (1:18)
- 3 Pillars Of Programming (3:32)
- Space Complexity (2:22)
- Exercise: Space Complexity (6:24)
- Exercise: Twitter (7:13)
- Optional: Javascript Loops (3:27)
- Section Summary (4:43)
- Let's Have Some Fun (+ More Resources)
How To Solve Coding Problems
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- Section Overview (5:04)
- What Are Companies Looking For? (3:05)
- What We Need For Coding Interviews (3:27)
- Exercise: Google Interview (2:31)
- Exercise: Interview Question (20:33)
- Exercise: Interview Question 2 (22:59)
- Review Google Interview (1:30)
- Optional Exercise: Google Interview On Your Own
- Section Summary (3:35)
- Unlimited Updates
Data Structures: Introduction
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Data Structures: Arrays
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- Arrays Introduction (13:51)
- Static vs Dynamic Arrays (6:40)
- Quick Note: Upcoming Video
- Optional: Classes In Javascript (24:51)
- Implementing An Array (17:19)
- Strings and Arrays (1:04)
- Exercise: Reverse A String (1:35)
- Solution: Reverse A String (10:31)
- Exercise: Merge Sorted Arrays (0:44)
- Solution: Merge Sorted Arrays (14:12)
- Interview Questions: Arrays
- Arrays Review (3:28)
- Implement a New Life System
Data Structures: Hash Tables
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- Hash Tables Introduction (4:10)
- Hash Function (5:56)
- Hash Collisions (9:43)
- Hash Tables In Different Languages (3:30)
- Exercise: Implement A Hash Table (3:51)
- Solution: Implement A Hash Table (17:24)
- keys() (6:11)
- Bonus: keys() Without Collision
- Hash Tables vs Arrays (2:01)
- Exercise: First Recurring Character (1:18)
- Solution: First Recurring Character (16:11)
- Interesting Tidbit: Python Dictionaries
- Hash Tables Review (6:09)
Data Structures: Linked Lists
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- Linked Lists Introduction (2:26)
- What Is A Linked List? (4:36)
- Exercise: Why Linked Lists? (2:05)
- Solution: Why Linked Lists? (5:35)
- What Is A Pointer? (5:45)
- Our First Linked List (8:38)
- Solution: append() (5:25)
- Solution: prepend() (2:27)
- Node Class (2:40)
- insert() (5:12)
- Quick Note: Upcoming Video
- Solution: insert() (13:08)
- Solution: remove() (5:21)
- Doubly Linked List (3:18)
- Exercise: Doubly Linked Lists
- Solution: Doubly Linked Lists (8:50)
- Singly vs Doubly Linked Lists (2:40)
- Exercise: reverse() (1:30)
- Solution: reverse() (7:38)
- Linked Lists Review (5:07)
- Exercise: Imposter Syndrome (2:55)
Data Structures: Stacks + Queues
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- Stacks + Queues Introduction (2:58)
- Stacks (3:28)
- Queues (3:30)
- Exercise: Stacks vs Queues (3:06)
- Solution: Stacks vs Queues (3:39)
- Quick Note: Upcoming Video
- Optional: How Javascript Works (24:12)
- Exercise: Stack Implementation (Linked Lists) (2:23)
- Solution: Stack Implementation (Linked Lists) (8:58)
- Exercise: Stack Implementation (Array) (0:53)
- Solution: Stack Implementation (Array) (3:56)
- Exercise: Queue Implementation (1:48)
- Solution: Queue Implementation (7:50)
- Queues Using Stacks (2:04)
- Stacks + Queues Review (2:19)
Data Structures: Trees
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- Trees Introduction (6:23)
- Binary Trees (5:45)
- O(log n) (7:00)
- Binary Search Trees (6:12)
- Balanced vs Unbalanced BST (3:42)
- BST Pros and Cons (2:26)
- Exercise: Binary Search Tree (3:57)
- Solution: insert() (10:10)
- Solution: lookup() (4:54)
- Bonus Exercise: remove() (2:28)
- Solution: remove() (7:41)
- AVL Trees + Red Black Trees (2:56)
- Resources: AVL Trees + Red Black Trees
- Binary Heaps (5:36)
- Quick Note on Heaps (1:08)
- Priority Queue (5:27)
- Trie (3:16)
- Tree Review (0:51)
Data Structures: Graphs
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Algorithms: Recursion
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- Introduction to Algorithms (3:51)
- Recursion Introduction (5:36)
- Stack Overflow (6:17)
- Anatomy Of Recursion (10:27)
- Exercise: Factorial (3:25)
- Solution: Factorial (6:20)
- Exercise: Fibonacci (1:59)
- Solution: Fibonacci (11:21)
- Recursive vs Iterative (4:16)
- When To Use Recursion (4:00)
- Exercise: Reverse String With Recursion
- Recursion Review (2:47)
Algorithms: Sorting
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- Sorting Introduction (7:01)
- The Issue With sort() (6:51)
- Sorting Algorithms (3:37)
- Bubble Sort (3:45)
- Exercise: Bubble Sort
- Solution: Bubble Sort (5:06)
- Selection Sort (2:39)
- Exercise: Selection Sort
- Solution: Selection Sort (2:23)
- Dancing Algorithms (1:36)
- Insertion Sort (2:38)
- Exercise: Insertion Sort
- Solution: Insertion Sort (2:06)
- Merge Sort and O(n log n) (8:59)
- Exercise: Merge Sort
- Solution: Merge Sort (4:44)
- Stable vs Unstable Algorithms
- Quick Sort (7:40)
- Optional Exercise: Quick Sort
- Which Sort Is Best? (4:40)
- Resources: Heap Sort
- Radix Sort + Counting Sort (4:17)
- Resources: Radix Sort + Counting Sort
- Exercise: Sorting Interview (1:27)
- Solution: Sorting Interview (7:07)
- Sorting In Your Language (1:27)
- Sorting Review (2:53)
Algorithms: Searching + BFS + DFS
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- Searching + Traversal Introduction (1:34)
- Linear Search (3:37)
- Binary Search (6:05)
- Graph + Tree Traversals (3:56)
- BFS Introduction (2:44)
- DFS Introduction (3:23)
- BFS vs DFS (3:20)
- Resources: BFS vs DFS
- Exercise: BFS vs DFS (0:44)
- Solution: BFS vs DFS (3:16)
- breadthFirstSearch() (9:15)
- breadthFirstSearchRecursive() (5:33)
- PreOrder, InOrder, PostOrder (5:21)
- depthFirstSearch() (12:03)
- Optional Exercise: Validate A BST
- Graph Traversals (3:53)
- BFS in Graph (2:07)
- DFS in Graph (2:49)
- Dijkstra + Bellman-Ford Algorithms (5:11)
- Searching + Traversal Review (4:21)
Algorithms: Dynamic Programming
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Non Technical Interviews
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- Section Overview (2:38)
- During The Interview (9:04)
- Exercise: Hero Stories
- Tell Me About Yourself (5:30)
- Exercise: Your Pitch
- Why Us? (5:06)
- Tell Me About A Problem You Have Solved (5:18)
- Exercise: Past Projects
- What Is Your Biggest Weakness (2:19)
- Exercise: Your Biggest Weakness
- Any Questions For Us? (3:24)
- Resources: Questions To Ask A Company
- Secret Weapon (8:11)
- After The Interview (5:24)
- Section Summary (3:56)
Offer + Negotiation
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Where To Go From Here?
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Extras: Google, Amazon, Facebook Interview Questions
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Contributing To Open Source To Gain Experience
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Bonus: Extra Bits
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