AI & Data
Deep Learning Challenges
Deep Learning challenges put you inside the work of building models that learn from raw data. You'll develop skills in Neural Networks and Feedforward Networks, apply Data Augmentation, and train models in PyTorch or TensorFlow alongside Reinforcement Learning fundamentals.
From there you'll handle the harder edges — Transformer architecture, Attention mechanisms, Custom architecture design, and Distributed training — working with PyTorch Lightning / Hugging Face Trainer, JAX research patterns, and Ablation study design the way research teams actually do. Each challenge you solve earns a verified credential you can share with recruiters.
Recommended Challenges
· PyTorch or TensorFlow Clear- ResearchSeniorNew
Diffusion-Policy Imitation for Bimanual Cooking Tasks
You receive 300 teleoperated demonstrations of a bimanual pour-and-stir task in a Robomimic-style simulator, deliberately including 2 valid solution modes per task (left-pour-ri…
- Diffusion Policies
- Imitation Learning
- Multimodal Action Distributions
Robot Learning - 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
- Supervised Learning
Meta-Learning, Transfer Learning, and Multi-Task Learning - CodeIntermediateNew
Build a Multilingual Customer-Email Classifier
You receive 28,000 labeled emails (skewed toward English and Mandarin). Try at least two approaches: (1) a fine-tuned multilingual transformer (XLM-RoBERTa or mDeBERTa) and (2) …
- Text Classification
- Multilingual NLP
- Hugging Face Transformers
Natural Language Processing - CodeIntermediateNew
Build a Domain-Specific Named-Entity Recognizer for Legal Contracts
Start from a strong English NER base (spaCy transformer or LegalBERT). Fine-tune on a provided 1,200-contract labeled dataset for the 9 entity types. Handle long contracts (ofte…
- Named Entity Recognition
- Sequence Labeling
- Domain Adaptation
Natural Language Processing 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
Evaluate VAEs vs. Diffusion for Synthetic Tabular-Data Generation
You receive a real labeled dataset (around 18,000 anonymized patient records, 32 features, binary outcome) and the team's existing VAE baseline. Train a tabular diffusion model …
- Tabular Diffusion
- Vae
- Synthetic Data
Generative AI - CodeBeginnerNew
End-to-End Lane Following on a Donkeycar Platform
Use the public Donkeycar Tub dataset (or collect about 30 minutes of driving on the simulator). Train a CNN-policy baseline (the Donkeycar default architecture is fine) that pre…
- End To End Learning
- Imitation Learning
- Pytorch Or Tensorflow
AI for Autonomous Vehicles - CodeIntermediateNew
Train an Object Detector for an Autonomous-Forklift Robotics Startup
You receive 12,000 labeled warehouse images (pallets, pedestrians, forklifts) plus a 1,500-image safety-test set heavy on pedestrian edge cases. Train an object detector (YOLOv8…
- Object Detection
- Yolo
- Edge Deployment
Deep Learning for Computer Vision - CodeBeginnerNew
Build a Video-Question-Answering Demo on a Budget
Pick the model (Video-LLaVA, VideoChat2, or LLaVA-Video) and justify on the A10G budget. Build a Streamlit demo: upload video, ask question, get answer with cited frame timestam…
- Video Language Models
- Multimodal Fusion
- Streamlit
Multimodal Machine Learning - 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.
- ResearchIntermediateNew
Evaluate a Knowledge-Graph-Augmented Recommender
You receive permission to use the public MovieLens 1M dataset plus a derived item-KG (movie -> genre, director, decade) built from Wikidata. Train two recommenders: a matrix-fac…
- Knowledge Graph Embeddings
- Recommender Systems
- Benchmarking
Knowledge Graphs and Semantic Web - CodeIntermediateNew
Segment Cells from Microscopy Images for a Pharma-AI Discovery Lab
You receive 3,500 microscopy images with pixel-level cell masks plus a 200-image hold-out set re-annotated by two biologists for inter-annotator agreement. Train a U-Net or SegF…
- Semantic Segmentation
- U Net
- Pytorch Or Tensorflow
Deep Learning for Computer Vision - CodeIntermediateNew
Fine-Tune ASR for a Healthcare Voice-Note Startup
You receive about 40 hours of de-identified clinician voice notes paired with corrected transcripts plus a medical-terminology lexicon (about 8,000 drug + procedure terms). Fine…
- Asr
- Speech Recognition
- Domain Adaptation
Speech Recognition and Spoken Language Processing - ResearchSeniorNew
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 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
Lane-Change Intent Classifier from Dashcam Video
Use a public driving video dataset (e.g., Argoverse 2 sensor or BDD100K) and curate ~6,000 short clips labeled with the three-class intent. Train a temporal model (e.g., a small…
- Video Understanding
- Temporal Modeling
- Model Evaluation
Visual Intelligence and Visual Reasoning - 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 - ResearchSeniorNew
Concept-Activation Vectors for an Autonomous-Vehicle Perception Audit
You receive a trained semantic-segmentation model (8 classes including pedestrian, vehicle, road, sky), an internal validation set of 2,500 driving frames, and a small concept-i…
- Tcav
- Concept Explanations
- Interpretability
Explainable and Interpretable AI - CodeIntermediateNew
Fine-Tune a Sequence-to-Sequence Model for Code-Doc Generation
Take a small base model (CodeT5+ or a distilled CodeLlama-Instruct). Build the dataset by mining around 8,000 high-quality function-docstring pairs from permissively-licensed Py…
- Seq2seq
- Hugging Face Transformers
- Fine Tuning
Neural Networks for NLP - 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 Or Tensorflow
Advanced Deep Learning - ResearchSeniorNew
Implement an Autoregressive Model for Anonymized Voice-Synthesis at a Defense Vendor
You receive a public-domain speech dataset (LibriTTS subset, around 50 speakers) and a fixed evaluation protocol (speaker-identifiability AUC, emotion-preservation MOS proxy, in…
- Autoregressive Models
- Voice Conversion
- Speech Synthesis
Deep Generative Models - 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 - ResearchSeniorNew
Audit a Production Model for Membership Inference Attacks
Use a black-box membership inference attack (e.g., the LiRA or shadow-model attack). You have query access to a sandboxed copy of the model + the original training data labels f…
- Membership Inference
- Privacy Attacks
- Model Evaluation
Privacy-Preserving Machine Learning - 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
- Hugging Face Transformers
- Pose Estimation
Machine Perception - CodeIntermediateNew
Build a Cross-Lingual Retrieval-Augmented QA System
Index around 5,000 internal-knowledge docs across the three languages using a multilingual embedding model (e.g., multilingual-e5 or BGE-M3). Build the retrieval-then-answer pip…
- RAG Architectures
- Cross Lingual Retrieval
- Multilingual Embeddings
Neural Networks for NLP - CodeIntermediateNew
Multi-Sensor Late-Fusion Prototype for an Indoor AGV
Use the public KITTI dataset (or a similar paired LiDAR+RGB dataset) restricted to static-obstacle classes. Implement a late-fusion baseline: a LiDAR-only detector (PointPillars…
- Sensor Fusion
- Object Detection
- Perception
AI for Autonomous Vehicles - CodeIntermediateNew
Actor-Critic for Energy-Storage Dispatch
You receive 3 years of hourly day-ahead price data and a Python simulator that models state of charge, round-trip efficiency, and a 1-day price forecast with documented uncertai…
- Actor Critic
- A2c
- Deep Rl
Reinforcement 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.
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