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.
- CodeBeginnerNew
Greedy Algorithm for Delivery-Slot Assignment
Receive 14 days of order data (around 4,800 orders) with timestamps, addresses (already geocoded), and slot preferences, plus rider rosters with shift starts, ends, and max work…
- Greedy Algorithms
- Algorithm Analysis
- Python Or Javascript
Algorithm Design and Analysis - AnalysisIntermediateNew
Amortized-Analysis Investigation of a Production Cache
Read the C++ cache source (around 1,800 lines, custom open-addressing with periodic resize-and-rehash). Perform amortized analysis using all three methods (aggregate, accounting…
- Amortized Analysis
- Functions & Data Structures
- Algorithm Analysis
Advanced Algorithms - CodeBeginnerNew
Shortest-Path Routing for a Bike-Share Operator
Receive the graph (nodes with lat/lon/elevation, edges with length and slope) and 50 origin-destination test pairs. Implement Dijkstra's algorithm with a custom edge-weight func…
- Graph Algorithms
- Dijkstra
- Algorithm Analysis
Algorithm Design and Analysis - 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 Or Javascript
Introduction to Artificial Intelligence 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
- CodeFoundationalNew
Optimize a Slow Search Function for a Recipe Marketplace
Receive the current Python function (nested loop over (recipe_title, ingredient_list) pairs), the 400k-row dataset (CSV), and 20 representative queries. Step 1: write up the cur…
- Algorithm Analysis
- Big O
- Functions & Data Structures
Algorithm Design and Analysis - CodeIntermediateNew
Randomized Sketch Algorithm for Stream Cardinality
Read the HLL paper (Flajolet et al., 2007) and a sample of 30 minutes of customer trace IDs (around 80M events). Implement HLL from scratch in Go (no library imports). Run bench…
- Randomized Algorithms
- Sketching
- Algorithm Analysis
Advanced Algorithms - AnalysisIntermediateNew
Spectral Clustering for Customer Segmentation at a SaaS
Receive a 12,000 customer × 220 feature usage matrix (counts per feature per week, averaged over 12 weeks). Construct a similarity graph (k-nearest-neighbors with k=15, Gaussian…
- Spectral Methods
- Linear Algebra
- Algorithm Analysis
Advanced Algorithms
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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