Model Evaluation
If you like applying Model Evaluation, every challenge here gives you a chance to practice it on a real industry brief.
- AnalysisBeginnerNew
Design a Churn-Prediction and Retention Model for TaskFlow
Using the TaskFlow customer dataset and the VP's framing memo (both provided), design and document a churn-prediction model. Perform exploratory analysis to surface patterns and…
- Logistic Regression
- Classification
- Feature Engineering
Open coursework - AnalysisIntermediateNew
Chest-X-Ray Deployment Audit Across Hospital Sites
You receive (1) a vendor-supplied multi-label chest-X-ray classifier, (2) the current single-site held-out evaluation set, (3) a 12,000-image multi-site evaluation set with 14-f…
- Medical Imaging
- Classification
- Model Evaluation
Open coursework - 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
Open coursework - AnalysisSeniorNew
Brain-Tumor MRI Segmentation Bake-Off
You receive a curated public multi-modal MRI brain-tumor cohort (~600 patients, T1/T1c/T2/FLAIR with whole-tumor / tumor-core / enhancing-tumor masks). Train all three architect…
- Medical Imaging
- Segmentation
- Convolutional Neural Networks
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
- AnalysisIntermediateNew
Transfer-Learning Backbone Bake-Off for Retail Product Tagging
You receive 80,000 retail product images tagged with multiple labels from a 250-tag taxonomy. Use each of the three pretrained backbones via two transfer strategies: (1) linear …
- Transfer Learning
- Fine Tuning
- Self Supervised Learning
Open coursework - AnalysisIntermediateNew
Build a Bayesian Credit-Scoring Model for an Emerging-Markets Fintech
You receive an anonymized snapshot of about 30,000 historical applications with features (income proxy, tenure on platform, prior loans, region) and the binary default outcome. …
- Bayesian Learning
- Credit Scoring
- Model Evaluation
Advanced Machine Learning - AnalysisBeginnerNew
Evaluate Speech-to-Text Quality for a Contact-Center Analytics Vendor
You receive 200 anonymized call-recording snippets (2-4 minutes each, ~67 per language) with reference transcripts plus a domain glossary of about 600 product terms. Run all thr…
- Speech Recognition
- Sequence Models
- Model Evaluation
Machine Perception - CodeIntermediateNew
Build a Sequence Model for Sign-Language Word Recognition
You receive about 12,000 short (1-3s) webcam clips covering a 50-word vocabulary, with body+hand pose features pre-extracted (e.g., MediaPipe Holistic landmarks per frame). Buil…
- Sequence Models
- Transformer
- Pose Estimation
Machine Perception - 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.
- 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
Open coursework - 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) - 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 - ResearchIntermediateNew
Multi-Task Learning for a Healthtech Triage Model
You receive 40,000 anonymized de-identified intake-form records with two labels: urgency tier (4 classes) and routed sub-specialty (12 classes). Train (1) two independent classi…
- Multi Task Learning
- Transfer Learning
- Transformer
Open coursework 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
- 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
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
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Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.



















































































