Algorithms & Data Structures

Implement Core Data Structures From Scratch with Complexity Analysis

Required. Implementing data structures from scratch is the prerequisite for algorithm complexity analysis — you cannot derive why Dijkstra's uses a min-heap without understanding heap operations. Build linked list, BST, hash table, heap, and graph before analysing algorithms that depend on them.

Implement 10 Classic Algorithms with Written Complexity Analysis

Required. Implement 10 classic algorithms (sorting, graph traversal, shortest path, dynamic programming) with written complexity analysis for each. This is the core UG CS competency — understanding why merge sort is O(n log n) in all cases while quicksort is O(n²) worst-case requires implementing both.

Prove Algorithm Correctness Using Formal Methods

Required. Proving algorithm correctness with loop invariants or induction distinguishes undergraduate CS depth from practical coding ability. This is the theoretical layer that the existing SKILLS path does not cover. Reviewer will ask you to prove a sixth algorithm you haven't prepared.

Achieve a Verified Competitive Programming Rating

Elective — the most AI-proof CS credential on the platform. Codeforces 1400+ OR LeetCode contest top 25%. Your public rating history with contest participation timestamps is proof of real-time algorithmic problem solving — it cannot be fabricated retroactively.

The standard algorithms textbook. Rigorous proofs, pseudocode, and complexity analysis for every major algorithm. The mathematical treatment here is what this path's correctness proof step is building toward.

Free, comprehensive reference for competitive programming algorithms with proofs and implementation guides. Covers everything from string algorithms to advanced graph theory. The standard reference for Codeforces preparation.

The platform for the competitive programming rating step. Start with Div 3 contests and work up to Div 2. Rating 1400 is the target — it represents reliably solving the A and B problems in Div 2 contests. Your public profile with rating history is the proof.

Free MIT course on algorithms with lecture videos, problem sets, and exams — no login, no paywall. Covers sorting, hashing, dynamic programming, and graph algorithms with rigorous complexity analysis. The standard academic treatment of everything on this path.