Computer Science
Programming Fundamentals Challenges
Programming Fundamentals challenges put you inside the work of writing code that is correct, readable and fast. You'll build core skills in functions & data structures, object-oriented design and design patterns, work in Python or JavaScript, and learn to do code reading and refactoring the way teams expect.
From there you'll tackle the harder edges — algorithm analysis, complexity analysis, graph algorithms and generics & type systems — pushing into performance engineering, low-latency programming patterns and systems-language proficiency (Go, Rust, C++). Each challenge you solve earns a verified credential you can share with recruiters.
- CodeFoundationalNew
Build a Best-First Search Solver for a Delivery Startup's Test Lab
Build a Python module exposing uniform-cost search and A-star search on a 2D grid with weighted cells (open road, traffic, no-go). Implement two admissible heuristics for A-star…
- Search Algorithms
- Heuristic Design
- Python
Introduction to Artificial Intelligence - CodeIntermediateNew
Implement and Tune HyperLogLog for Trace-Stream Cardinality in Go
Working from the HyperLogLog paper (provided as a real source) and the provided representative trace sample, implement HyperLogLog from scratch in Go with no third-party algorit…
- Randomized Algorithms
- Sketching
- Algorithm Analysis
Open coursework - CodeBeginnerNew
Design an Effort-Aware Bike Routing Feature for Lisbon
Working only from the provided materials — the Lisbon street-graph edges (lisbon-bike-graph), the matching node coordinates and elevations (lisbon-graph-nodes), the 50 origin-de…
- Graph Algorithms
- Dijkstra
- Algorithm Analysis
Open coursework - AnalysisSeniorNew
Amortized-Analysis Investigation of a Production Telemetry Cache
Working only from the three provided materials — the de-identified incident record (incident-record), the representative cache source module (cache-source), and the recorded ope…
- Amortized Analysis
- Data Structures
- Algorithm Analysis
Open coursework Practice your coursework on real scenarios.
Every challenge is shaped from real-world context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- DesignBeginnerNew
Greedy Delivery-Slot Assignment for a Munich Grocery Startup
Using the provided order history sample, rider roster, and manual dispatch baseline, design and implement a greedy slot-assignment algorithm in Python. The algorithm must (1) so…
- Greedy Algorithms
- Algorithm Analysis
- Python
Open coursework - AnalysisIntermediateNew
Spectral Clustering Proposal for Customer Segmentation at Cadence
Using the provided customer usage sample, construct a similarity graph (k-nearest-neighbors with k=15 and Gaussian radial-basis-function edge weights), compute the normalized gr…
- Spectral Methods
- Linear Algebra
- Algorithm Analysis
Open coursework - CodeFoundationalNew
Diagnose and Rebuild a Slow Recipe Search at a Marketplace Startup
Work only from the three items in the provided materials: the current search function, a representative sample of the recipe catalog, and the fixed set of representative queries…
- Algorithm Analysis
- Big O
- Data Structures
Open coursework
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
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