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
- CodeSeniorNew
Coordinate a Fleet of Warehouse Robots
Implement a simulated warehouse grid with 80 robots solving a pick-and-deliver workload. Design a decentralized coordination protocol (recommend a contract-net or auction-based …
- Multi Agent Coordination
- Decentralized Algorithms
- Simulation
Open coursework - AnalysisIntermediateNew
Harden a Medium-Voltage Grid Against Storm-Season Failures
Build a network model of the medium-voltage service area from the provided node and edge datasets (roughly 1,600 nodes and 1,900 links, each link carrying capacity, install year…
- Network Science
- Graph Analysis
- Resilience Analysis
Open coursework - AnalysisIntermediateNew
Auditing Bias in a Fintech Credit Scoring Model
Conduct a quantitative fairness audit using a public proxy dataset (e.g., the UCI Adult or Give Me Some Credit dataset re-framed as BNPL decisions) and apply at least three fair…
- Algorithmic Fairness
- Ai Audit
- Regulatory Analysis
AI, Ethics and Society - 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 Develop in-demand professional skills.
Each challenge names the skills it strengthens. Over time, your profile fills with the competences a hiring manager would actually look for.
Why Ewance
- CodeBeginnerNew
Predict Catalyst Properties for a Green-Hydrogen Pharma Spinout
Use an open catalyst dataset (e.g., Open Catalyst Project subset, or a Materials Project pull) where each candidate has descriptors and a target activity property. Train a tabul…
- Tabular Modeling
- Uncertainty Quantification
- Feature Engineering
AI for Science and Engineering - StrategyBeginnerNew
Plot a Diversification Path for a Nairobi Skincare Brand
Using the founder's company case file, the product portfolio sales dataset, and the category attractiveness readout provided to you, run a portfolio analysis (the BCG growth-sha…
- Portfolio Analysis
- Market Research
- Strategic Thinking
Open coursework - StrategyBeginnerNew
Scope a Demand-Forecasting Model with Operations Stakeholders
You receive recorded interview transcripts (or summary notes) for the three personas, plus a sample of the historical sales data. Map each stakeholder's pain to candidate ML pro…
- Stakeholder Framing
- Ml Problem Scoping
- Metric Design
Machine Learning in Practice - ResearchSeniorNew
Neuromarketing Audit for a Sustainable Fashion Retailer
Your team will design and simulate a neuromarketing experiment. First, propose two alternative store layouts (e.g., circular vs. grid) and two website homepage designs (e.g., he…
- Neuromarketing
- Experimental Design
- Eye Tracking Analysis
Consumer Behavior - Browse challenges
Explore role
Pricing Strategist
Set the price that captures value without leaving sales on the table. Demand modelling, willingness-to-pay research, and the disciplined experimentation that turns pricing into a competitive advantage.
- ResearchSeniorNew
Compare RNN vs Transformer for Long-Sequence Modeling
Pick a public trajectory dataset (e.g., Argoverse 2, Waymo Open, or ETH-UCY). Implement three models with comparable parameter counts (around 5M each): an LSTM baseline, a vanil…
- Transformers
- Rnn
- State Space Models
Open coursework - ResearchBeginnerNew
Evaluate a Generative AI Image Tool with a Within-Subjects Study
You will write a study protocol, recruit 20 participants (a Discord callout is fine), counterbalance the two conditions, and run 45-minute sessions over Zoom. Collect three meas…
- Experiment Design
- User Study
- Within Subjects Design
Human-Computer Interaction for AI Systems - CodeBeginnerNew
Optimize Wind-Turbine Layout with a Genetic Algorithm
You receive a wind-speed-and-direction time series for the lease area, the polygon boundary, a minimum inter-turbine spacing constraint, and a Jensen wake model. Implement a rea…
- Genetic Algorithms
- Metaheuristics
- Constraint Handling
Open coursework - DesignSeniorNew
Design a Multi-Objective Dynamic Pricing Engine for CityRide
Acting as a data scientist on CityRide's pricing team, design and prototype a dynamic pricing engine that, given the live time, pickup zone, and supply-demand conditions, quotes…
- Reinforcement Learning
- Optimization
- Simulation
Open coursework Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- 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 - CodeSeniorNew
Grounded Language for a Robotics Pick-and-Place Demo
Use a tabletop simulator (PyBullet or Isaac Sim, both open) with 5 object types and 5 spatial relations (left of, right of, behind, in front of, on top of). Curate or generate a…
- Grounded Language Understanding
- Semantic Parsing
- Perception
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 - AnalysisIntermediateNew
Map Knowledge Diffusion Across an Open-Source Project Ecosystem
Using the de-identified contributor activity export (material 1), build a temporal contributor-project network from the recorded events, then collapse it into a contributor-to-c…
- Network Science
- Temporal Networks
- Graph Analysis
Open coursework - AnalysisIntermediateNew
Cache Coherence Protocol Comparison on a Multicore Simulator
Stand up gem5's Ruby coherence framework with both MESI and MOESI protocols on a 16-core configuration. Run the 6-benchmark suite (provided): producer-consumer queue, false-shar…
- Cache Coherence
- Multicore Architecture
- Simulation
Advanced Computer Architecture - AnalysisBeginnerNew
Redesign Glow Naturals' Mumbai Last-Mile Delivery Network
Using the delivery records in 'GN-DELIVERY-LOG', the operational account in 'GN-OPS-FILE', and the unit costs and constraints in 'GN-COST-AND-CONSTRAINTS', diagnose where Glow N…
- Route Optimization
- Cost Benefit Analysis
- Supply Chain Design
Open coursework - ResearchSeniorNew
Train Cooperative Agents with Multi-Agent RL
Pick an open multi-agent environment (PettingZoo's MPE 'simple_spread', Overcooked-AI, or SMAC). Implement or wrap three methods: IPPO (independent PPO per agent), MAPPO (centra…
- Multi Agent Reinforcement Learning
- Ppo
- Pytorch
Open coursework - StrategyBeginnerNew
Reprice the Hero Serum for a Copenhagen Beauty Startup
Using the competitor price list, the customer purchase history, and the willingness-to-pay survey results provided to you, recommend a single new shelf price for the vitamin C s…
- Game Theory
- Pricing Strategy
- Market Analysis
Open coursework - AnalysisBeginnerNew
Digital Banking App Feature Prioritization
You are part of the product team. Analyze the neobank's user transaction data (anonymized CSV provided), conduct a competitive analysis of similar features at eToro, Lemonade, a…
- Product Analysis
- Data Analysis
- Competitive Analysis
Fintech and Digital Finance - 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 - StrategyFoundationalNew
Restructure GreenMart's Store Sales Force to Lift Upselling
Using the provided transaction-level sales export, the staff roster and turnover record, and the store-visit field notes, build a sales force restructuring plan for GreenMart's …
- Sales Force Analysis
- Incentive Design
- Training Program Design
Open coursework - DesignBeginnerNew
Redesign Weekly Production Scheduling for a Munich Craft Brewery
Using the historical demand dataset, the production-constraints specification, and the current-operations snapshot provided, design a single weekly production schedule for the t…
- Process Analysis
- Capacity Planning
- Scheduling
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.



















































































