Algorithms Boot Camp Topics
An outline of all the most important topics for studying algorithms
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This is the full study guide for the Algorithms Boot Camp and meant to be a complete roadmap for everything you need to know about algorithms.
As I write more notes, I’ll link to them here.
Array
Problems
two sum
search index
kth largest element in array
Concepts
2d arrays
nd arrays
jagged array
Linked list
Operations
Insert
Delete
Find
Reverse
counting
finding middle
merging
kth to last note
detecting cycles
Stack
Towers of Hanoi
Queue
LIFO
FIFO
Tree
Concepts
root
edge
leaf
depth
Binary Tree
Binary Search Trees
Problems
level order traversalre
construct tree from traversal
Balanced tree
AVL Tree
b-tree
Operations
Insertion
Deletion
Traversal
Pre order
in order
post order
Search
Breadth First Search
Depth First Search
find min/max
find successor predecessor
Hash table
Implementations
Array
Linked List
Binary Tree
Operations
get
put
delete
Hash Function
Linear Probing
Quadratic Probing
Collision Resolution
Problems
lru cache
Heap
Priority queue
heap
Compare function
enqueue
dequeue
peek
Concepts
complete binary tree
priority queue
array representation
Min Heap
Max Heap
Operations
build
insert
get
delete
heapify
heap sort in place
Problems
merge k sorted lists
kth largest element in array
the skyline problem
Trie
compressed trie
suffix trie
Advanced data structures
skip list
suffix tree
suffix array
bloom filter
Sorting
insertion sort
merge sort
quick sort
radix sort
sort stability
counting sort
Problems
dutch national flag
merge two sorted arrays
Graph
Concepts
Graph theory
Pathfinding
Connectivity
Shortest Path
Minimum Spanning Tree
Cycles
disjoint graph
Operations
Traversal
Breadth First Search
Depth First Search
bipartite graph
topological sort
djikstra’s algorithm
bellman-ford
Floyd-Warshall algorithm
Prim’s algorithm
Kruskal’s algorithm
Graph Representations
adjacency list
adjacency matrix
Recursion
Concepts
Backtracking
Base Case
Recursive Case
Inductive Step
Tail Recursion
Memoization
Problems
recursive factorial
recursive exponent
subsets of size n
fibonacci numbers
pascals triangle
towers of hanoi
combinatorial enumeration of binary strings
letter case permutations
subsets 1
permutations 1
permutations 2
subset sum
generate parenthesis
n queens
subarray sum equals k
valid parentesis
String Algorithms
Concepts
String matching
Pattern matching
String search
Data compression
Edit distance
Substring search
String similarity measures
Operations
rabin karp
kmp knuth morris pratt
Problems
non repeating characters
anagram
palindrome
frequency counting
reverse
Dynamic Programming
Problems
0/1 knapsack
longest common subsequence
subset sum
mimimum edit distance
minimum numbers of coins
longest increasing subsequence
longest palindromic subsequence
text justification
Computational Geometry
Network Flow Algorithms
network flow
maximum flow
minimum cut
Ford–Fulkerson
Edmonds–Karp
Dinic’s algorithm
König’s theorem
NP-Complete
Approximation
Simulated annealing
Tabu search
Genetic algorithms
Ant colony optimization
Particle swarm optimization
Cross-entropy method
Examples of NP Problems
Set Cover
Knapsack
Bin Packing
Shortest Path
Maximum Flow
Minimum Cut
Vertex Cover
Hamiltonian Path
Traveling Salesman
Satisfiability Problem
Partition Problem
Clique Problem
Chromatic Number Problem
Search
linear search
binary search
Depth-first search
Breadth-first search
Best-first search
A* search
Dijkstra’s algorithm
Bellman-Ford algorithm
Floyd-Warshall algorithm
Johnson’s algorithm
Algorithm Design
Greedy algorithms
Dynamic programming
Divide and conquer
decrease and conquer
transform and conquer
Randomized algorithms
Algorithm Analysis
Harmonic series
aritmetic geometric series
Time Complexity
big-O notation
Omega notation
Theta notation
little-o notation
arithmetic series
harmonic series
arthmetic geometric series
Space Complexity
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