Complexity Classes
Classifications of computational problems by resource requirements, including P, NP, and NP-complete.
Algorithms
CPU Scheduling
Operating system algorithms that determine which process or thread runs on the CPU, including FCFS, SJF, Round Robin, and priority-based …
Divide and Conquer
An algorithmic paradigm that recursively breaks a problem into smaller subproblems, solves them independently, and combines the results.
Dynamic Programming
An algorithmic technique that solves complex problems by breaking them into overlapping subproblems and storing their solutions.
Graph Algorithms
Algorithms for traversing and finding paths in graphs, including BFS, DFS, Dijkstra's, and A*.
Greedy Algorithms
Algorithms that make the locally optimal choice at each step, aiming for a globally optimal or near-optimal solution.
Hash Tables
Data structures that map keys to values using hash functions for near-constant-time lookup, insertion, and deletion.
Heaps and Priority Queues
Tree-based data structures that efficiently support finding and extracting the minimum or maximum element.
Linked Lists, Stacks, and Queues
Fundamental linear data structures for organizing and accessing data sequentially.
Recursion and Backtracking
Self-referential functions and systematic trial-and-error with pruning for exploring solution spaces.
Search Algorithms
Algorithms for finding elements in data structures, including linear search, binary search, and interpolation search.
Strategy Pattern
A behavioral design pattern that defines a family of algorithms, encapsulates each one, and makes them interchangeable at runtime.
Trees and Binary Search Trees
Hierarchical data structures including BSTs, AVL trees, red-black trees, and B-trees for efficient searching and storage.
Data Structures for AI Applications
Arrays, hash maps, trees, graphs, queues, and vector stores - how the choice of data structure shapes the performance of AI pipelines.
Sorting and Search Algorithms for AI Pipelines
How sorting and search algorithms underpin AI pipeline design: complexity trade-offs, partial sorting for top-k selection, tiered analysis …
Time Complexity and Big-O Notation
An introduction to Big-O notation and how it describes the asymptotic behavior of algorithms.