Experimental design
If you like applying Experimental design, every challenge here gives you a chance to practice it on a real industry brief.
- ResearchIntermediateNew
Hands-on Lab: Reproduce a Recent SOTA Vision Paper
Pick one of three pre-approved 2025 papers (offered by the supervisor) with a known reference codebase you may consult but not copy. Re-implement the model and training loop in …
- Pytorch Or Tensorflow
- Paper Reproduction
- Experimental Design
AI/ML Practicum and Hands-on Lab - ResearchIntermediateNew
Lab Project: Compare Three Architectures on Your Own Mini-Benchmark
Scope the problem yourself (suggested examples: sentiment classification on a niche domain, tabular anomaly detection, time-series forecasting on a public dataset). Define the t…
- Experimental Design
- A/B Testing With Statistical Significance
- Pytorch Or Tensorflow
AI/ML Practicum and Hands-on Lab - ResearchIntermediateNew
Run a Perceptual Study on Color Scales for a Climate Risk Map
Design a remote study (Prolific or similar, 60 participants screened for normal color vision via Ishihara plates online) with 3 task types: (1) value estimation, (2) anomaly det…
- Perceptual Study
- Color Scales
- Experimental Design
Information and Data Visualization - CodeIntermediateNew
Train a Deep Q-Network for Warehouse Robot Routing
You receive a Gymnasium-compatible warehouse simulator (50x50 grid, 8 dynamic obstacle pedestrians, 20 randomized pick locations) and a baseline A* planner script. Train a DQN a…
- Deep Q Learning
- Reinforcement Learning
- Pytorch Or Tensorflow
Deep Reinforcement Learning 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
- 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 - ResearchIntermediateNew
Train a NeRF for Real-Estate Virtual Tours
You receive a curated dataset of 3 apartments, each with around 120 input images and known camera poses (already SfM-processed). Train a NeRF variant (Instant-NGP or Nerfacto re…
- Neural Scene Representation
- Nerf
- Pytorch Or Tensorflow
3D Vision and Multi-View Geometry - 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
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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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.