PyTorch Or TensorFlow
If you like applying PyTorch Or TensorFlow, every challenge here gives you a chance to practice it on a real industry brief.
- ResearchExpertNew
Reproduce a Mechanistic Interpretability Result on a Small Transformer
Pick a published mechanistic-interpretability paper that operates on a small (under 1 billion parameter) open-source transformer (e.g., GPT-2 small, Pythia 70M). Set up the envi…
- Mechanistic Interpretability
- Transformer Internals
- PyTorch Or TensorFlow
AI Safety and Alignment - CodeExpertNew
Train a Reinforcement-Learning Policy for Drone Obstacle Avoidance
You receive a custom Gymnasium drone-flight environment (provided), a baseline hand-engineered controller, and a target evaluation suite covering 4 obstacle densities. Train a P…
- Reinforcement Learning
- Ppo
- Robotics Simulation
Advanced Robotics - ResearchExpertNew
Benchmark Long-Context Architectures on a Legal-Doc Retrieval Task
You receive a public legal-QA dataset (e.g., LongBench's legal split or similar) filtered to documents over 50,000 tokens. Implement or wrap 3 architectures: a sliding-window Tr…
- Long Context Architectures
- State Space Models
- Hugging Face Transformers
Advanced Deep Learning - CodeIntermediateNew
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 Or TensorFlow
Advanced Deep 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
- ResearchAdvancedNew
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 - ResearchAdvancedNew
Kernel Methods vs. Deep Learning on a Tiny-Data Drug-Discovery Task
You receive (or download) 3 public ADMET datasets from MoleculeNet (e.g., BBBP, Lipophilicity, FreeSolv). For each, train both: (a) a Gaussian process with a Tanimoto kernel ove…
- Kernel Methods
- Gaussian Processes
- Neural Networks
Advanced Machine Learning - CodeAdvancedNew
Finetune a Diffusion Model for Sustainable-Fashion Mockups
You receive 1,200 product photos with paired captions and the brand's style guide. Fine-tune a Stable-Diffusion-class base model with LoRA (Low-Rank Adaptation, a parameter-effi…
- Diffusion Models
- Lora Finetuning
- PyTorch Or TensorFlow
Advanced Deep Learning - CodeExpertNew
Train a Manipulation Policy for Bin Picking with Imitation Learning
You receive a dataset of 500 teleop trajectories on the in-distribution part plus a held-out simulation environment with a never-seen part. Train an imitation-learning policy (D…
- Imitation Learning
- Manipulation
- Diffusion Policy
Advanced Robotics - 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.
- ResearchExpertNew
Investigate Why Our Generative Model Memorizes Training Data
Pick a small open-source diffusion model (e.g., a Stable-Diffusion-class community model trained on LAION-subset). Reproduce a published membership-inference + extraction probe …
- Generative Models
- Memorization Analysis
- Differential Privacy
Advanced Deep Learning - ResearchAdvancedNew
Train a Physics-Informed Neural Network for Heat Transfer in a Battery Pack
Solve the 2D unsteady heat-conduction equation on a square cell cross-section with a localized source and Dirichlet boundary conditions on the casing. Implement a baseline finit…
- Physics Informed Neural Networks
- Partial Differential Equations
- PyTorch Or TensorFlow
AI for Science and Engineering - ResearchExpertNew
Validate a Foundation Model for Protein-Ligand Docking Acceleration
Pick 20 publicly available protein-ligand complexes from the PDBbind dataset (or similar public source). Use a published open-source structural foundation model (e.g., a Boltz-s…
- Foundation Model Evaluation
- Structural Biology
- Model Validation
AI for Science and Engineering - ResearchAdvancedNew
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 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
- ResearchExpertNew
Price American Options with a Deep Hedging Notebook
Simulate price paths for a single underlying (geometric Brownian motion is fine as a baseline; bonus for stochastic volatility). Implement Longstaff-Schwartz Monte Carlo as the …
- Deep Learning
- Stochastic Modeling
- Derivatives Pricing
AI and Quantitative Finance - AnalysisAdvancedNew
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 - CodeAdvancedNew
Build a Neural Surrogate for Computational Fluid Dynamics in HVAC Design
Use a published CFD dataset (e.g., AirfRANS or a small in-house dataset if available) of around 1,000 steady-state airflow simulations on 2D building zones. Train a Fourier Neur…
- Neural Operators
- Surrogate Modeling
- Computational Fluid Dynamics
AI for Science and Engineering - AnalysisAdvancedNew
Structured Prediction for Insurance Claim Triage
You receive 18,000 historical claims with text, attachments-count, claim amount, customer tenure, and the ground-truth final routing bucket. Train a structured classifier (e.g.,…
- Structured Prediction
- Multi Class Classification
- Model Evaluation
Advanced Machine Learning - ResearchExpertNew
Pretrain a Small Vision Transformer with Self-Supervised Learning
You receive 80,000 unlabeled 224x224 histology tiles plus 4,000 labeled tiles split into train/val/test. Pretrain a ViT-Small using a self-supervised method of your choice (DINO…
- Supervised Learning
- Vision Transformers
- PyTorch Or TensorFlow
Advanced Deep 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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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.