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.
CodeBeginnerNewBuild a Pricing-Aware Scheduling Agent for Smart Thermostats
Using only the materials provided, build an intelligent agent with four working parts: perception (read the sensor history), learning (cluster each household's comfort intervals…
- Intelligent Agents
- Basic Learning
- Python Programming
Open coursework- AnalysisBeginnerNew
Build a Topic-Modeling Pipeline for Citizen Feedback
Take the 60,000 comments (anonymized). Build a BERTopic pipeline with multilingual sentence embeddings (Catalan + Spanish + occasional English). Tune number-of-topics via topic-…
- Topic Modeling
- Bertopic
- Multilingual NLP
Open coursework - AnalysisBeginnerNew
Build a Reproducible Pricing Analysis for a DTC Skincare Brand
You receive 24 months of order-line data (around 480,000 lines), a Shopify-style customer export, and a discount-code log. Build a Python pipeline that produces: SKU-level price…
- Data Wrangling
- Exploratory Data Analysis
- Cohort Analysis
Applied Data Analysis and Practical Data Science - AnalysisIntermediateNew
Run a Pre-Deployment Fairness + Drift Audit on a Hiring Model
You receive a trained classifier (joblib), the training data sample, and a held-out 'next-month' evaluation set. Compute group fairness metrics (false-positive-rate gap, true-po…
- Fairness Metrics
- Drift Detection
- Bias Mitigation
Machine Learning in Practice 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
Classify Retail Product Photos for an E-Commerce Marketplace
Use a publicly-available product-image dataset (e.g., Fashion-MNIST extended, or a Kaggle e-commerce subset of around 10k images across 12 categories). Fine-tune a small pretrai…
- Image Classification
- Transfer Learning
- Pytorch
Open coursework - CodeIntermediateNew
Build a CodeQL Query Pack to Catch Logging of Personal Data
Using the provided personal-data source and logging-sink specification, write CodeQL data-flow queries for Java and Python that detect personal data travelling from a source (re…
- Static Analysis
- Codeql
- Data Flow Analysis
Open coursework - AnalysisBeginnerNew
Optimize Hyperparameters with Bayesian Optimization on a Tight Budget
You receive a B2B-SaaS churn dataset (about 12,000 customer-month rows, 38 features) and a fixed sweep budget of 40 trials per model family. Implement a Bayesian optimizer (Optu…
- Bayesian Optimization
- Hyperparameter Tuning
- Ensemble Methods
Advanced Machine Learning - CodeIntermediateNew
Build a Feature Store Backbone for a Healthtech ML Team
You receive synthetic wearable telemetry (heart rate, accelerometer, sleep stages) for around 5,000 patients across 90 days, plus the existing scattered feature scripts from the…
- Feature Engineering
- Data Modeling
- Python
Data Engineering and Big Data Systems - Browse challenges
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Marketing Analyst
Plan and measure campaigns that grow the business. Funnel analytics, attribution, segmentation, and the rigorous measurement that lets marketing defend its budget at the leadership table.
- CodeIntermediateNew
Ship a Knapsack Battery Allocator for Farm Sensors
Using the device specification (device-spec), the sensing-mode table (sensing-modes), the month of simulated farm days (simulated-farm-days), and the reference greedy heuristic …
- Dynamic Programming
- Algorithm Analysis
- C Programming
Open coursework - CodeBeginnerNew
Image Search for a DTC Furniture Retailer's App
Use a pretrained vision-embedding model (CLIP ViT-B/32 or DINOv2-small). Index a catalog of around 1,500 furniture images. Curate a small evaluation set of around 50 user-style …
- Image Embeddings
- Vision Transformers
- Image Search
Open coursework - ResearchIntermediateNew
Disease-Progression Modelling for a Neurodegeneration Biotech
You receive a curated longitudinal Parkinson's cohort (about 1,200 patients, 4-12 visits each, MDS-UPDRS sub-scores, cognitive assessments, demographics). Fit (1) a linear mixed…
- Disease Progression Modeling
- Mixed Effects Models
- State Space Models
Open coursework - AnalysisBeginnerNew
Map Creator Communities for a Short-Form Video Platform
You receive a 90-day sample of about 4 million creator-creator interactions (duets, mentions, audience overlap) and creator metadata (region, language, content tag). Build a cre…
- Network Analysis
- Community Detection
- Graph Visualization
Open coursework Build a verifiable portfolio.
Submissions become evidence. Reviewers with shipping experience score against a rubric; the result becomes a credential anyone can verify.
Why Ewance
- AnalysisSeniorNew
Backtest a Gilt-Versus-Corporate-Bond Spread Strategy
Using the supplied two-year daily market-history dataset of gilt and corporate-bond yields, prices, and bid-ask spreads, design and backtest a long-short relative value strategy…
- Fixed Income Arbitrage
- Yield Spread Analysis
- Backtesting
Open coursework - AnalysisBeginnerNew
Predict 30-Day Churn for a Direct-to-Consumer Cosmetics Brand
Working only from the two materials you are given (a subscriber behavior sample dataset and a one-page stakeholder brief from the head of retention), build a binary classificati…
- Python
- Scikit Learn
- Logistic Regression
Open coursework - AnalysisBeginnerNew
Build a Public Open-Data Dashboard for Urban Mobility
Pull the city's open-data cyclist-collision dataset (10 years of incidents, geocoded). Define a clear before/after window around the protected-lane rollout, control for traffic-…
- Exploratory Data Analysis
- Data Wrangling
- Geospatial Analysis
Applied Data Analysis and Practical Data Science - 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
Plan Inventory Replenishment as an MDP for an E-Commerce AI Startup
You receive 18 months of daily demand for 50 representative SKUs at one warehouse plus lead-time and unit-cost data. For one SKU at a time, formulate an MDP with state = (on-han…
- Mdp Modeling
- Value Iteration
- Dynamic Programming
Open coursework - AnalysisFoundationalNew
Cluster Climate-Tech SMB Customers for a Growth Team
You receive a CSV with company size, industry sub-vertical, country, product features adopted, monthly active users, and lifetime value. Standardize features, decide on a cluste…
- Unsupervised Learning
- Clustering
- Dimensionality Reduction
Machine Learning (Undergraduate) - CodeIntermediateNew
Plan Warehouse Pick Routes with a Classical Planner
You receive a stylized warehouse map (aisle graph), 30 sample shifts of pick tasks, and the current heuristic's outputs. Write a PDDL domain + problem generator, solve with at l…
- Pddl Modeling
- State Space Search
- Classical Planning
Open coursework - CodeBeginnerNew
Responsive Web Redesign for SaaS Scale-up
You are to redesign the TaskFlow website's homepage, pricing page, and a new 'Enterprise' landing page. The redesign must be responsive (mobile-first) and built with HTML/CSS/JS…
- Html
- Css
- Javascript
Open coursework - AnalysisBeginnerNew
Right-Size a Real-Time Recommendation Serving Cluster
You receive 7 days of request-level telemetry (timestamp, latency, error code, pod) plus the existing Horizontal Pod Autoscaler (HPA) and node-group configs. Analyze traffic pat…
- Model Serving
- Kubernetes
- Autoscaling
Machine Learning at Scale - ResearchSeniorNew
SAT-Based Planner for Smart-Grid Demand Response
Encode the dispatch problem (which customers to curtail by how much, respecting per-customer contractual caps and grid-cell totals) as a SAT or MaxSAT instance. Solve 50 histori…
- Sat Based Planning
- Constraint Encoding
- Benchmarking
Automated Planning - AnalysisBeginnerNew
Interpretable-by-Design GAM for an Insurer's Claims Triage
You receive an anonymized claims dataset (around 60,000 claims, target: log reserve), a feature schema (22 features), and an existing LightGBM baseline (held-out R^2 of 0.78). T…
- Generalized Additive Models
- Ebm
- Interpretability
Explainable and Interpretable AI - CodeIntermediateNew
Simulating Queueing for a 40-Person SaaS Support Team
Build a discrete-event simulation of the ticket handling process: tickets arrive randomly (Poisson), are triaged, then assigned to specialists (tier 1 and tier 2). Calibrate usi…
- Simulation
- Queueing Theory
- Python
Operations Analytics and Optimization
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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