Big O Notation
Master time and space complexity to mathematically prove why your solution is efficient.
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Intermediate to Advanced
8 weeks
30 hours
Course overview
Data Structures & Algorithms
Master the core foundations of computer science. Learn to write optimized, efficient code, recognize patterns, and ace technical interviews with confidence.
Estimated duration: 8 focused weeks combining theory, visualization, and challenging logic puzzles.
24
Lessons
8
Modules
50+
Challenges
O(n²)
Array Input
{ }
Hash Map
/ \
Tree Sort
⚡
O(1) Output
What You'll Learn
Six essential computer science pillars designed to transform the way you approach complex code.
Linear Structures
Understand how Arrays, Linked Lists, Stacks, and Queues handle data sequentially in memory.
Hash Maps & Sets
Unlock the power of O(1) constant time lookups to massively speed up brute-force solutions.
Trees & Graphs
Traverse hierarchical and networked data using Breadth-First and Depth-First Search algorithms.
Sorting & Searching
Implement Binary Search and understand the mechanics behind Merge Sort and Quick Sort.
Dynamic Programming
Break down overlapping subproblems using memoization and tabulation to optimize recursive calls.
🌐 OpenGraph
Explore the Full DSA Learning Map
Discover advanced system design concepts, technical interview prep guides, and what comes next.
Course TrisGraph
A structured, scannable roadmap showing exactly how the data structures and algorithms interlock.
Module 1
Mathematical Foundations & Asymptotic Analysis
Module 2
Module 3
Non-Linear Memory: Linked Lists, Stacks & Queues
Module 4
Searching, Sorting & Algorithmic Paradigms
Module 5
Hash Tables & Advanced Collections
Module 6
Module 7
8-Week Study Planner
A structured pacing model to build muscle memory without algorithmic burnout.
Foundations
Internalize Big O Notation, master Array manipulations, and learn String algorithms.
Pointers & Maps
Trade space for time using Hash Maps, and learn pattern recognition with Linked Lists and Two-Pointers.
Trees & Recursion
Shift to non-linear data. Understand recursion deeply by navigating Binary Search Trees and Heaps.
Graphs & DP
Tackle the hardest interview concepts: navigating Graphs and optimizing overlapping subproblems with DP.
Milestone Challenges
Apply your theoretical knowledge by writing algorithms to solve these standard technical problems.
Two Sum Visualizer
Optimize an O(n^2) nested loop into an elegant O(n) Hash Map solution.
Open ChallengeValid Parentheses
Implement a LIFO Stack to parse and validate structural string groupings.
Open ChallengeMaze Solver
Use Breadth-First Search (BFS) to find the shortest path through a 2D matrix.
Open ChallengeRoute Optimizer
Build an engine using Dijkstra's Algorithm and a Priority Queue to calculate the cheapest network route.
Open CapstoneReady to master Algorithms?
Start with Memory Architecture & Pointers build up your problem-solving toolkit.