AI & Data
Statistics & Data Science Methods Challenges
Statistics & Data Science Methods challenges put you inside the work of drawing trustworthy conclusions from data. You'll build Statistics Fundamentals and Statistical Analysis, run Exploratory Data Analysis, Hypothesis Testing, Confidence Intervals, and Linear Regression, and design clean Sampling Methods.
From there you'll handle the harder edges — Bayesian methods, Causal inference, A/B testing with statistical significance, Monte Carlo Simulation, and Uncertainty Quantification — applying Experimental design the way data scientists actually do. Each challenge you solve earns a verified credential you can share with recruiters.
Recommended Challenges
- All
- Data Analysis
- Experimental design
- Simulation
- Exploratory Data Analysis
- Statistical Analysis
- Uncertainty Quantification
- Logistic regression
- Cost Modeling
- Hypothesis Testing
- Monte Carlo Simulation
- A/B testing with statistical significance
- Linear Regression
- Time series basics
- Bayesian methods
- Causal inference
- Sampling Methods
- AnalysisIntermediateNew
Simulate Hospital Bed Allocation for a Healthtech Decision Support Pilot
You receive 12 months of anonymized admissions and discharges data plus ward layouts (medicine, surgery, ICU, geriatrics) and a small set of clinical transfer rules. Build a dis…
- Discrete Event Simulation
- Simpy
- Policy Comparison
Decision Support Systems and Decision Analysis - AnalysisBeginnerNew
Optimizing Ad Spend for a D2C Cosmetics Brand
You are a data analyst at Glow & Grow. Using the provided dataset (simulated), perform an exploratory data analysis to understand trends in ad performance. Build a regression mo…
- Data Analysis
- Regression
- Data Visualization
Open coursework - ResearchFoundationalNew
Diagnose GreenBite's Plant-Based Chicken Launch Readiness
Work only from the four items in the provided materials: the GreenBite launch-readiness case file, the draft consumer survey instrument left by the previous analyst, the nationa…
- Survey Design
- Data Analysis
- Consumer Behavior
Open coursework - ResearchSeniorNew
Long-Context QA Evaluation Benchmark for Legal Memoranda
You receive 25 anonymized legal memoranda (50-90 pages each) and 100 QA pairs whose answers are deliberately spread across the documents (25 in pages 1-20, 25 in pages 20-40, 25…
- Long Context Qa
- Benchmark Design
- Model Evaluation
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
- DesignSeniorNew
Social Security Compliance for a Remote-First Tech Company
As a compliance analyst, you must audit GlobalDev's current practices and propose a system for social security registration and contribution tracking across multiple EU jurisdic…
- Social Security Law
- EU Regulation
- Cross Border Compliance
Labor and Employment Law - AnalysisIntermediateNew
Design an Electronic Health Record Data-Quality Audit
Stand up a Python (pandas + DuckDB) audit notebook ingesting the 14M-record extract. Define and run quality checks across four dimensions: completeness (required-field missingne…
- Health Informatics
- Data Quality
- Snomed Ct
Computational Biology and Health Informatics - CodeBeginnerNew
Calibrate a Demand Forecast with Bayesian Confidence Intervals
You receive 24 months of weekly demand for 600 SKUs plus the existing XGBoost point predictions. Fit a Bayesian conformal-prediction layer (or, alternatively, a Gaussian-Process…
- Bayesian Inference
- Uncertainty Quantification
- Conformal Prediction
Probabilistic Machine Learning - AnalysisBeginnerNew
Cache Configuration Study for a Memory-Bound Workload
Profile the existing inner loop on a workstation with perf to baseline L1/L2/L3 miss rates and miss latencies. Run the same loop through gem5's classic cache model under 6 confi…
- Caches
- Memory Subsystems
- Performance Modeling
Computer Architecture - Browse challenges
Explore role
Product Manager
Ship product that solves real user problems. Combine user research, prototyping, and stakeholder alignment to turn ambiguous briefs into measurable wins — the role at the centre of modern software teams.
- AnalysisIntermediateNew
Decarbonizing a 40-Person SaaS Scale-Up's Supply Chain
As a carbon management analyst, you must quantify CloudSync's current carbon footprint (Scope 1, 2, 3), identify reduction levers, and propose a roadmap to carbon neutrality. Co…
- Carbon Footprinting
- Scope 3 Emissions
- Renewable Energy
Open coursework - AnalysisSeniorNew
Real Options Analysis for Ørsted Offshore Wind Expansion
Construct a base-case DCF for a 1.1 GW US offshore wind project using public assumptions on capex/MW, capacity factor, and PPA pricing. Then layer a real options framework: mode…
- Real Options
- Monte Carlo Simulation
- DCF Modeling
Advanced Corporate Finance - AnalysisIntermediateNew
Forecasting Churn for a SaaS Scale-Up
You are a data scientist intern at TaskFlow. Using the provided dataset, perform feature engineering and build a logistic regression or decision tree model to predict churn. Ide…
- Data Analysis
- Regression
- Classification
Open coursework - ResearchIntermediateNew
Reproduce a Vision-Model Paper Under a Reproducibility Standard
Pick a vision-model paper from CVPR or NeurIPS 2024-2025 with publicly available code and a manageable compute footprint (single-GPU under 24 hours). Reproduce the headline metr…
- Reproducibility
- Experimental Design
- Model Evaluation
AI Measurement and Evaluation 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
- ResearchBeginnerNew
Optimizing Onboarding for a Fintech App
Your task is to analyze the current onboarding flow, identify drop-off points, and propose a redesigned onboarding experience. You will use user behavior data (provided in a sim…
- User Research
- Ux Design
- Data Analysis
Product Management - ResearchIntermediateNew
Testing Market Efficiency in European Tech IPOs
Your task is to collect daily stock prices for 30 European tech IPOs from the first 60 trading days post-listing. Compute cumulative abnormal returns (CAR) using a market model …
- Event Study
- Abnormal Returns
- Market Model
Open coursework - AnalysisIntermediateNew
Detect Coordinated Inauthentic Behavior on a National News Platform
Receive an anonymized 90-day export of comments (user_id, article_id, timestamp, like_count, reply_to_id) and basic user metadata (registration date, login pattern bucket). Buil…
- Network Science
- Community Detection
- Graph Analysis
Open coursework - AnalysisBeginnerNew
Diagnose and Optimize Inventory for a Milan Cosmetics Brand
Work only from the two materials you are given: a daily sales dataset covering the past twelve months for the ten products, and a parameters brief listing each product's price, …
- Excel Modeling
- Vba Programming
- Demand Forecasting
Open coursework - StrategyBeginnerNew
Pitch a Regulatory Sandbox Application for an Edtech AI Product
Read the EU AI Regulation's regulatory-sandbox provisions. Pick a member-state sandbox program (Spain, Norway-as-EEA, or a German-state pilot are publicly documented options) an…
- Regulatory Analysis
- Ai Governance
- Product Strategy
Open coursework - CodeIntermediateNew
Designing a Dynamic Pricing Engine for a Ride-Hailing Startup
Your team is given a dataset of historical rides (timestamp, pickup location zone, demand level, available drivers). You must design a pricing algorithm that: (1) uses a multipl…
- Python
- Pandas
- Simulation
Programming for Business Applications - ResearchSeniorNew
Experimental Design for a Fintech App's Savings Nudge
You are a behavioral data scientist at SaveSmart. Design a randomized controlled trial (RCT) to test the effect of a 'future self' nudge on savings behavior. Define treatment an…
- Experimental Design
- Statistical Analysis
- Nudge Theory
Behavioral Economics - 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 - 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 - CodeBeginnerNew
Behavior Cloning for a Pick-and-Place Manipulator
You receive 200 human teleoperated demonstrations (state + action trajectories) of picking 8 small electronic components from a tray and placing them at marked locations in a ro…
- Behavior Cloning
- Imitation Learning
- Manipulation
Open coursework - ResearchSeniorNew
Certify Robustness for a Medical-Imaging Classifier
You receive the classifier (a PyTorch ResNet variant) and a 4,000-image labeled validation slice. Apply randomized smoothing (Cohen et al.) at sigma in {0.25, 0.5, 1.0}. Report …
- Certified Robustness
- Randomized Smoothing
- Formal Verification
Trustworthy AI, Robustness, and Safety - CodeSeniorNew
Triage Brain-CT Stroke Detector with Calibrated Uncertainty
You receive a curated public head-CT dataset (about 2,800 scans, slice-level labels for hemorrhagic stroke) and a held-out 600-scan hospital cohort. Train a 3D CNN or 2.5D slice…
- Medical Imaging
- Convolutional Neural Networks
- Uncertainty Quantification
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.
Industry 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.



















































































