Data Sciences Challenges
Explore data science challenges on Ewance to build skills employers expect from analysts and ML engineers. Work through challenges on data cleaning, exploratory analysis, modeling, and storytelling with data.
Most Popular
- CodeBeginnerNew
Build a Robust Image Classifier for a Climate-Tech Satellite Startup
You receive a labeled dataset of about 25,000 Sentinel-2 patches (positive = illegal construction visible, negative = not). The dataset is split by region AND by season so you c…
- Data Augmentation
- Deep Learning
- Pytorch
Advanced Deep Learning - CodeBeginnerNew
Stack Five Models for a Kaggle-Style Forecasting Bake-Off
You receive a pseudonymized dataset of 24 months of daily shipment volumes across about 200 origin-destination lanes plus weather and holiday features. Train 5 base models, use …
- Ensemble Methods
- Time Series Forecasting
- Feature Engineering
Advanced Machine Learning - 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 - AnalysisBeginnerNew
Audit a Hiring-Screening Model for Demographic Bias
You receive: (a) inference API access to the production model (black-box), (b) a 12,000-resume audit benchmark with self-declared gender and age-band labels (consented, GDPR-com…
- Fairness Metrics
- Bias Auditing
- Model Evaluation
AI Ethics, Fairness, and Responsible AI 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
- DesignBeginnerNew
Draft a Model Card for a Generative Image Product
You receive the model's training-data summary, evaluation metrics, intended-use statement, and known failure modes from the ML team. Write: (a) a 3-page plain-language model car…
- Model Cards
- Transparency Documentation
- Responsible Ai
AI Ethics, Fairness, and Responsible AI - StrategyBeginnerNew
Design an Internal AI-Use Policy for a Mid-Cap Bank
You receive the bank's existing IT-acceptable-use policy and a description of which AI tools are being rolled out (an internal Anthropic Claude wrapper for general use; a code-c…
- Ai Governance
- Policy Design
- Responsible Ai
AI Ethics, Fairness, and Responsible AI - DesignBeginnerNew
Design the Onboarding for a Consumer-AI Copilot App
You receive: current funnel analytics (1M trial sign-ups over the last 90 days, current activation rate, current D1/D7/D30 retention), a competitor teardown deck, and the founde…
- Product Design
- User Onboarding
- Experimentation
AI for Business and AI Product Management - AnalysisBeginnerNew
Analyze a Learning-Analytics Dataset for At-Risk Detection
You receive an anonymized dataset of LMS engagement features (logins, assignment submissions, forum posts, video-watch time), grade history, and a binary label for end-of-semest…
- Learning Analytics
- Classification
- Fairness Metrics
AI in Education and Learning Analytics - 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.
- 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
AI and Quantitative Finance - 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 - CodeBeginnerNew
Implement a Constraint Solver for a Lisbon Tourism Scheduler
Model the next-week schedule as a CSP: variables are (guide, day, slot) assignments; domains are available routes; constraints encode language requirements, max consecutive tour…
- Constraint Satisfaction
- Backtracking Search
- Python
Introduction to Artificial Intelligence - CodeBeginnerNew
Reason about Drone Mission Plans with Probabilistic Logic
Build a small Bayesian network (around 12 nodes) capturing weather, no-fly-zone proximity, battery state, operator certification, and mission risk. Implement exact inference (va…
- Bayesian Networks
- Probabilistic Inference
- Knowledge Representation
Introduction to Artificial Intelligence Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- PresentationBeginnerNew
Evaluate Intelligent Agents in a Sustainable-Logistics Simulation
Build a small grid-world simulation where a delivery agent must complete 10 stops while respecting traffic, charging needs, and time windows. Implement three classical agent des…
- Intelligent Agents
- Simulation Design
- Python
Introduction to Artificial Intelligence - CodeBeginnerNew
Compare MDP Solvers for a Smart-Grid Battery Dispatch Pilot
Model home-battery dispatch as a finite MDP: state is (state-of-charge, hour-of-day, current price tier), actions are charge/hold/discharge with realistic efficiency losses, tra…
- Markov Decision Processes
- Value Iteration
- Policy Iteration
Artificial Intelligence: Principles and Techniques - 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
AI Law, Policy, and Regulation - CodeBeginnerNew
Build a Fairness Evaluation Harness for a Credit-Score Model
Implement a Python module that, given model predictions, ground truth, and group identifiers, computes demographic parity difference, equal-opportunity difference, predictive-pa…
- Algorithmic Fairness
- Statistical Evaluation
- Python
AI Measurement and Evaluation - AnalysisBeginnerNew
Diagnose Churn Drivers for a B2B SaaS Workflow Tool
You receive three CSV exports: 18 months of weekly product-usage events for about 1,800 accounts, the full support-ticket history, and account firmographics (industry, size, pla…
- Exploratory Data Analysis
- Data Wrangling
- Feature Engineering
Applied Data Analysis and Practical Data Science - 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 - AnalysisBeginnerNew
Audit a Climate-Tech Sensor Dataset for Production Readiness
You receive 18 months of raw sensor readings from 1,200 sensors (about 800M rows), plus a sensor-metadata table (location, firmware version, deployment date). Profile the data f…
- Data Quality Audit
- Data Profiling
- Time Series Analysis
Applied Data Analysis and Practical Data Science - 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
Tune a Recommender for an EU Streaming Music App
Use the public Last.fm-360k or similar dataset (anonymized listening histories) as a stand-in. Implement a baseline matrix-factorization recommender, then a hybrid that adds tra…
- Recommender Systems
- Feature Engineering
- Model Evaluation
Applied Machine Learning - CodeBeginnerNew
Ship a Lightweight ML Microservice for an EdTech Reading App
You receive 3 months of session telemetry (around 50M reading events, child-anonymized). Engineer features per session window, train a small classifier (logistic regression base…
- Feature Engineering
- Model Serving
- Containerization
Applied Machine Learning - CodeBeginnerNew
End-to-End Lane Following on a Donkeycar Platform
Use the public Donkeycar Tub dataset (or collect about 30 minutes of driving on the simulator). Train a CNN-policy baseline (the Donkeycar default architecture is fine) that pre…
- End To End Learning
- Imitation Learning
- Pytorch
AI for Autonomous Vehicles - CodeBeginnerNew
GPU Cost Dashboard for an AI Consulting Practice
Pull AWS Cost and Usage Report, GCP billing export, and Lambda Labs invoices into a single Parquet table. Implement a tagging convention (project + client + experiment_id) and a…
- Cloud Cost Attribution
- Etl Pipelines
- Data Modeling
Cloud Computing for Data and ML
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.