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Coachable Training Vault
Week 1: Python Fundamentals and Object Oriented Programming
Why Python
Python Tips and Fundamentals (43:34)
Functions in Python
Object Oriented Programming in Python
Python Style Guide
Pass By Reference and Assignment
Comparing Objects and Built In Functions
Optional Arguments
Week 2: Runtime Analysis, Linked Lists, Stacks and Queues
Helpful Math Concepts for Programming
Bits, Bytes and Binary - Other Number Systems
Runtime and Space Complexity (36:36)
The Doubling Principle - Tips for Runtime Analysis
Analyzing Runtime in Nested Loops/Functions
Linked List (55:05)
Stacks/Queues (53:12)
Week 3: Hash Maps, Deque, Recursion
Hash Maps - Theory (35:10)
Deque / LRU Cache (82:13)
Recursion - Introduction (48:32)
Recursion - Binary Search (34:20)
Memory/Space Complexity in Recursion
Why Recurrences Are Important
Solving Recurrence Relationships
Week 4: Strings and Sorting Algorithms
Tips for Using Strings in Interviews
Palindromes (18:32)
Anagrams (14:57)
Simple Sorts (15:41)
Merge Sort (28:32)
Quick Sort (12:00)
Mergesort is the best. Why do we need the others?
Sorting with Counts (30:02)
Substring Search / Pattern Matching
Week 5: Binary Trees, Tries
Recursion - Binary Tree Traversals (16:29)
Recursion - Binary Search Trees (BST) (93:23)
Tries (32:12)
Week 6: Graphs, Heaps
Graphs - Introductions (21:09)
Graph - BFS/DFS (64:59)
Graphs - Cycles and Topological Sort (25:25)
Eventual Safe States - Topological Sort (43:21)
Proofs and Logic
Priority Queues / Heaps (65:58)
Minimum Spanning Trees and Forests
Djikstra's Algorithm
Week 7: Dynamic Programming
Dynamic Programming (72:10)
Week 8: Algorithm Review and Teachable Final
Essential Programming Techniques
Algorithms Cheat Sheet
Reductions
Patterns in Interviews Questions
Last Minute Review of Algorithms
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Analyzing Runtime in Nested Loops/Functions
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