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.
- ResearchIntermediateNew
Compare Kernel Methods to Trees on a Genomics Classification Task
You receive a curated benchmark of about 12,000 labeled variants with ~120 numerical + ~40 string features. Fit kernel SVMs (RBF, polynomial, string), random forest, and XGBoost…
- Kernel Methods
- Svm
- Tree Ensembles
Open coursework - 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 - CodeBeginnerNew
Forecast Hourly Energy Demand for a Microgrid Operator
You receive 24 months of hourly demand, weather (temperature, irradiance), and calendar data for the community. Build a probabilistic forecaster (e.g., quantile regression with …
- Probabilistic Forecasting
- Quantile Regression
- Deep Forecasting
Open coursework - CodeIntermediateNew
Agentic RAG with Context-Window Budgeting
You receive a synthetic dataset of 60 founder-style queries paired with 'workspaces' (each up to 500 documents across 3 source types), plus gold-standard answers and citation li…
- Agentic RAG
- Context Window Management
- Iterative Retrieval
Retrieval-Augmented Generation 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
- CodeBeginnerNew
Build a Credit-Card Fraud Detector for a Singapore Neobank
You receive 9 months of anonymized authorization data (around 8 million transactions, around 0.4 percent fraud) plus current rule outcomes. Split temporally and train at least t…
- Classification Modeling
- Class Imbalance
- Model Calibration
Open coursework - CodeIntermediateNew
Multi-Agent Research Assistant for Biotech Patent Review
You receive 20 historical patent applications with the firm's own prior-art memos as ground truth. Design and build a 3-agent system: (a) Searcher — issues queries to a patent-s…
- LLM Agents
- Multi Agent Collaboration
- Agent Evaluation
AI Agents and LLM-Based Agents - DesignIntermediateNew
Train a Self-Play Agent for a Card-Game Edtech Demo
Implement a small two-player imperfect-information card game (Kuhn poker or a 3-card simplified Hold'em variant). Implement CFR or CFR+ for the game and run self-play for at lea…
- Counterfactual Regret Minimization
- Self Play
- Game Theory
Open coursework - CodeIntermediateNew
Build a Forgetting-Curve-Aware Spaced-Repetition Engine
You receive 6 months of practice logs from 8,000 learners (item, timestamp, response correctness, response latency). Fit a learner-personalized forgetting model (logistic per-it…
- Spaced Repetition
- Personalization
- Behavioral Data
Open coursework - Browse challenges
Explore role
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.
- DesignIntermediateNew
Design a Continuous Eval Pipeline for an Enterprise RAG Product
Design (and partially build) a continuous-eval pipeline for a RAG system: (1) a structured eval set with at least 50 queries grouped by query class; (2) automated scoring (LLM-a…
- Continuous Evaluation
- LLM Evaluation
- Retrieval Augmented Generation
AI Measurement and Evaluation - CodeIntermediateNew
Ship an MVP RAG Knowledge Assistant for a Climate-Tech Startup
As a 4-person team across a 6-week sprint, ship: (1) an ingestion pipeline for around 4,000 mixed PDFs and markdown files; (2) a vector store with documented chunking strategy; …
- Retrieval Augmented Generation
- Software Engineering For Ai
- Vector Databases
AI Software Engineering Group Project - 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 - CodeBeginnerNew
Build Semantic Search for an Internal Engineering Wiki
You receive a Confluence XML export (~12k pages, ~80 MB of text) and a hand-labeled benchmark of 50 internal queries with ground-truth doc IDs. Chunk and embed the corpus with a…
- Embedding Models
- Vector Search
- Pgvector
Vector Databases and Embeddings 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
- DesignIntermediateNew
Design a Negotiation Protocol for Trading Agents
Choose a negotiation framework (alternating-offers Rubinstein, monotonic concession, or auction-based) and justify against the freight use case. Implement a simulator in Python …
- Agent Negotiation
- Game Theory
- Multi Agent Systems
Multi-Agent Systems - CodeBeginnerNew
Churn-Prediction Model for a B2B Vertical SaaS
Use 18 months of anonymized data (provided) covering: usage events, login frequency, support tickets, NPS responses, billing health, feature adoption, practice firmographics. De…
- Supervised Learning
- Python Programming
- Ml Applications
Machine Learning (CS Elective) - CodeIntermediateNew
Forecast Intraday FX Volatility for a London Liquidity Desk
You receive 18 months of tick-level mid-quote data for six FX pairs plus a calendar of scheduled macro events. Resample to 1-minute bars, engineer realized-volatility features, …
- Time Series Forecasting
- Feature Engineering
- Model Validation
Open coursework - DesignBeginnerNew
Design a Negotiation Support Tool for Climate-Tech Supplier Contracts
You will design and prototype a negotiation support tool for a single supplier contract with six issues (price per kg, delivery lead time, minimum order quantity, payment terms,…
- Negotiation Modeling
- Decision Support Systems
- Multi Issue Bargaining
Open coursework - AnalysisBeginnerNew
Customer-Segmentation Study for a DTC Subscription Box
Use 18 months of anonymized data: order history, churn events, NPS responses, box-rating data, referral activity, marketing-channel attribution. Engineer features (RFM-style + b…
- Unsupervised Learning
- Python Programming
- Ml Applications
Machine Learning (CS Elective) - 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 - CodeSeniorNew
Plan Under Uncertainty for a Warehouse Restocking Robot
You receive a discrete-event simulator of a 1,200-shelf warehouse with calibrated optical-scanning error rates and stock-out cost per shelf. Formulate the restocking decision as…
- Planning Under Uncertainty
- Pomdp
- Monte Carlo Planning
Advanced Robotics - AnalysisBeginnerNew
Approximate Inference for a Topic Model on Customer Tickets
You receive 180,000 tickets (subject + body) spanning the last 18 months. Preprocess into a bag-of-words representation with sensible stopwords and bigrams. Fit a 20-topic LDA v…
- Variational Inference
- Latent Dirichlet Allocation
- Approximate Inference
Open coursework - CodeIntermediateNew
Detect Coordinated Fraud Rings via Link Analysis at a Neobank
You receive 90 days of account, login, and transaction data (around 1.2 million accounts, around 30 million events) plus a labeled set of 80 known fraud rings. Build a multi-rel…
- Graph Analysis
- Community Detection
- Link Analysis
Open coursework - AnalysisBeginnerNew
Audit Safety Stops for a Cafe-Service Robot Pilot
You receive 30 days of logs covering 240 near-miss events (close approach to a human, low-battery emergency, network loss). For each event, classify whether the safety stop trig…
- Safety Analysis
- Incident Review
- Failure Mode Analysis
Robotics 
CodeBeginnerNewBuild a Search-Based Delivery Router for a Madrid Grocery Startup
Build a Python service that exposes a single /route endpoint. It accepts a courier's starting location, a list of delivery stops, and a traffic window, and returns the stops in …
- Search Algorithms
- Intelligent Agents
- Python Programming
Open coursework- DesignIntermediateNew
Build a Feature Store for a Fintech Fraud Team
You will design a feature-store layer covering 12 representative fraud features (account-level, merchant-level, transaction-level), with both batch (Spark) and online (low-laten…
- Feature Stores
- Data Pipelines
- Spark
Machine Learning at Scale
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.
Related skill families
Browse all skillsIndustry teams behind a decade of practitioner briefs
Hiring from this pool?
Sponsor a challenge and meet candidates through actual work.
Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.