Competitive Programming

Advanced Algorithms: Competitive Programming

From School Math to Olympiad Math & Math for CS. Master the mental models of elite problem solvers.

IntermediateDr. Anna SmithEnglish12 Weeks

What You Will Learn

Complexity

Deep dive into Big-O, Master Theorem, and resource optimization strategies.

DP

Master state transitions, memoization, and complex space-reduction techniques.

Graphs

Advanced flow networks, shortest paths, and topological pattern matching.

Greedy

Local optimality proofs and constructing efficient greedy architectures.

Course Description

This course is designed for serious students who want to bridge the gap between theoretical computer science and competitive problem solving. We do not just teach you the code; we teach you how to invent the algorithm.

Why this course is different

Focus on mathematical derivation before implementation.
Real-world case studies from IOI, ICPC, and Google Code Jam.
Phygital worksheets that connect abstract graph theory to physical models.

Example Complexity Focus

// Optimizing recursive state
dp[i][j] = min(dp[i-1][j], dp[i][j-1]) + cost[i][j];
// Reduced from O(N*M) to O(N) space complexity

Prerequisites

Discrete MathematicsC++ or Python BasicsBasic Data Structures

Frequently Asked Questions

Is this course suitable for beginners?

No, this is an intermediate-to-advanced course. You should have a solid grasp of at least one programming language and basic discrete math concepts.