Drift Detection
If you like applying Drift Detection, every challenge here gives you a chance to practice it on a real industry brief.
- DesignAdvancedNew
Visualize Embedding Drift for a RAG Knowledge Assistant
You receive weekly snapshots over 12 weeks of around 50,000 document embeddings each (1024-dim). Design and build a visualization tool that: (a) projects each snapshot to 2D wit…
- Embeddings
- Dimensionality Reduction
- Umap
Data Visualization - AnalysisAdvancedNew
Audit a Sepsis Early-Warning Model for Subgroup Performance
You receive a pre-trained vendor model, the training-data summary, and a held-out hospital-network evaluation set (about 18,000 ICU stays with sepsis labels). Compute AUROC + AU…
- Model Evaluation
- Fairness Metrics
- Model Calibration
Machine Learning for Healthcare and Biomedicine - DesignAdvancedNew
Drift-Detect + Self-Heal a Multi-Tenant Kubernetes Estate
Enable ArgoCD auto-sync with selfHeal + prune across all 28 clusters. Add Kyverno cluster policies enforcing baseline standards (registry, resource limits, network policy). Buil…
- Argocd
- Kyverno
- Drift Detection
GitOps and Continuous Delivery - AnalysisAdvancedNew
Run a Pre-Deployment Fairness + Drift Audit on a Hiring Model
You receive a trained classifier (joblib), the training data sample, and a held-out 'next-month' evaluation set. Compute group fairness metrics (false-positive-rate gap, true-po…
- Fairness Metrics
- Drift Detection
- Bias Mitigation
Machine Learning in Practice 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
- AnalysisAdvancedNew
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
Machine Learning for Imaging and Medical Image Analysis
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.