Computer & Information Sciences
Data Science Challenges
Real data-science projects and challenges on Ewance — clean messy datasets, build and evaluate models, and turn raw data into decisions the way a working data scientist does. Solve them to build a portfolio of verified, recruiter-checkable proof you can do the work — not just describe it.
Recommended challenges
- StrategyBeginnerNew
AI Make-or-Buy Analysis for a Climate-Tech Series-B
You receive: the company's headcount and ML capability map, vendor RFP responses from 3 vendors per category, and 18-month strategic context. For each model category, build a ma…
- Ai Workforce Strategy
- Make Or Buy Analysis
- Vendor Evaluation
AI for Business and AI Product Management - CodeIntermediateNew
Temporal Planner for a Robotics Mission Operator
You receive 30 days of mission logs with task lists, time windows, and actual durations. Encode the planning problem with temporal PDDL (PDDL 2.1 durative actions) and solve wit…
- Temporal Planning
- Pddl Modeling
- Simulation
Automated Planning - 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 - CodeIntermediateNew
Triage Medical-Imaging Annotations with a Small Vision Model
Train a binary normal/abnormal classifier on the public CheXpert or NIH ChestX-ray14 dataset. Use temperature scaling to calibrate the output, then define abstention thresholds …
- Cnn Classification
- Transfer Learning
- Calibration
Applied Machine Learning Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- ResearchIntermediateNew
Sim-to-Real Domain Randomization for a Mobile Robot
You receive an Isaac Sim navigation environment, a baseline trained policy, a 50-episode real-bench test set (recorded sensor streams + ground truth) for offline policy evaluati…
- Domain Randomization
- Sim To Real
- Robot Navigation
Robot Learning - CodeIntermediateNew
Prototype Constitutional-AI Style Guardrails for an Internal Chatbot
Author a 'constitution' of 15 to 20 principles tailored to internal research use (no IP leakage, no off-label medical claims, no personnel-data fishing, etc.). Implement a criti…
- Constitutional Ai
- Alignment Techniques
- LLM Evaluation
AI Safety and Alignment - 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 - CodeIntermediateNew
DPO Fine-Tune for a Domain-Specific Writing Assistant
You receive a base instruction-tuned model checkpoint plus 2,500 preference pairs from editorial reviews (each pair: two grant-application paragraphs, the editor-preferred winne…
- Dpo
- Preference Learning
- Model Finetuning
Machine Learning from Human Preferences (RLHF and Alignment) - 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.
- CodeBeginnerNew
Prototype a Multimodal Visual-Question-Answering Demo
You will use a small open-source vision-language model (e.g., LLaVA-1.5-7B or PaliGemma) and prompt-engineer it for the warehouse-VQA task. Build a Gradio web demo. Construct a …
- Vision Language Models
- Multimodal Perception
- Prompt Patterns
Machine Perception - CodeIntermediateNew
Description-Logic Reasoner for Insurance-Policy Coverage Checks
You receive 50 representative coverage rules in plain English (from the current rule engine) and a sample of 1,000 anonymized claim cases with the current engine's outcomes (cov…
- Description Logics
- Owl
- Reasoning
Fuzzy Logic, Knowledge Representation, and Symbolic Reasoning - 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) - PresentationIntermediateNew
Design a Hybrid Symbolic-Neural Agent for an Enterprise RAG Demo
Design a hybrid agent for a 'company-policy assistant' demo: a symbolic planner decomposes user goals into typed subtasks ('find policy', 'check applicability', 'compose answer'…
- Hybrid Ai
- Symbolic Planning
- RAG Architectures
Artificial Intelligence: Principles and Techniques 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
- CodeIntermediateNew
Design a Visual Search Backend for a Boutique Luxury Marketplace
You receive a catalog of 80,000 luxury items (image + sparse metadata) and a labeled query set of 300 user photos with hand-picked target items. Choose an embedding strategy (CL…
- Visual Search
- Word Embeddings
- Clip
Deep Learning for Computer Vision - 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 - DesignIntermediateNew
Stand Up a Feature Store for a Series-B Fintech
Pick one priority feature group (recommend the 25 transaction-history features used by the fraud model). Define the offline source-of-truth (likely Snowflake or BigQuery), the o…
- Feature Store
- Feature Engineering
- Airflow Dags
ML Engineering and Production ML - CodeBeginnerNew
Build a Crop-Disease Classifier for a Smallholder Agritech Startup
You receive a curated 22,000-image cassava-disease dataset across 5 classes (4 diseases + healthy) plus a labeled 1,200-image held-out test set. Train a CNN classifier (start wi…
- Cnn Classification
- Cnn Architectures
- Transfer Learning
Deep Learning for Computer Vision - DesignIntermediateNew
Design a Real-Time Order Pipeline for a Fintech Payments Platform
You receive a synthetic Kafka stream of around 500 transactions per second, a static merchant dimension table (about 80,000 rows), and a daily FX rate snapshot. Design an end-to…
- Streaming Data
- Kafka Event Streaming
- Stream Processing
Data Engineering and Big Data Systems - ResearchBeginnerNew
Case-Study Analysis of a Public AI Incident
Pick one public AI incident (suggestions: a chatbot's harmful response that went viral, a facial-recognition false-arrest case, a financial-model bias scandal). Produce a 6-page…
- Incident Analysis
- Responsible Ai
- Case Study Research
AI Ethics, Fairness, and Responsible AI - CodeIntermediateNew
Implement Model Predictive Control for a Delivery Robot
You receive a kinematic bicycle model of the robot, a published track layout, and 30 minutes of recorded waypoint trajectories. Implement a nonlinear MPC controller using acados…
- Model Predictive Control
- Optimal Control
- Robotics Simulation
Advanced Robotics - 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 Database Basics
- Pgvector
Vector Databases and Embeddings - DesignFoundationalNew
Stakeholder Workshop on AI Risk for a Public-Sector Pilot
You receive a description of the pilot (24/7 LLM chatbot answering questions on municipal services in Spanish and Catalan). Design a 3-hour workshop for around 25 mixed-stakehol…
- Stakeholder Management
- Workshop Design
- Responsible Ai
AI Ethics, Fairness, and Responsible AI - AnalysisBeginnerNew
Cluster a Telco's Subscriber Base for a Pricing Refresh
You receive 12 months of anonymized subscriber-level data: monthly minutes, SMS, mobile data, top-up frequency, top-up amount, churn flag, and tenure. Clean and feature-engineer…
- Clustering
- Feature Engineering
- Exploratory Data Analysis
Data Mining and Knowledge Discovery - AnalysisIntermediateNew
Compare Stereo Depth Methods for a Drone Inspection Startup
You receive 500 calibrated stereo pairs from a turbine inspection plus sparse LiDAR ground truth on each pair. Implement (or wrap) three depth estimators: OpenCV Semi-Global Mat…
- Stereo Depth Estimation
- Multi View Geometry
- Model Evaluation
3D Vision and Multi-View Geometry - AnalysisIntermediateNew
A/B Testing for a 40-Person SaaS Scale-up Moving to Enterprise
You are a data analyst at TaskFlow. You are given the raw A/B test data (visitor logs, conversions, and downstream sales data). Your task is to perform a rigorous analysis: chec…
- A/B Testing
- Statistical Analysis
- Bayesian Methods
Data Science for Business
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.