AI & Data
Computer Vision Challenges
Computer Vision challenges put you to work teaching machines to see. You'll develop skills in Image Processing and CNN Classification, build pipelines with OpenCV, tackle Object detection and Segmentation, and adapt pretrained models through Transfer learning.
From there you'll handle the harder edges — Custom architectures, 3D vision, Real-time inference, and Computer Graphics — building and deploying vision systems the way applied research teams actually do. Each challenge you solve earns a verified credential you can share with recruiters.
- DesignIntermediateNew
Rescue a 3x3 Convolution Accelerator on Zynq UltraScale+
Working only from the materials provided, reach and defend an engineering judgment, then deliver the working accelerator that proves it. Read the engineering case file ('vision-…
- Systemverilog
- Fpga
- Axi Stream
Open coursework - CodeFoundationalNew
Classify Retail Product Photos for an E-Commerce Marketplace
Use a publicly-available product-image dataset (e.g., Fashion-MNIST extended, or a Kaggle e-commerce subset of around 10k images across 12 categories). Fine-tune a small pretrai…
- Image Classification
- Transfer Learning
- Pytorch
Open coursework - CodeIntermediateNew
Triage Medical-Imaging Annotations with a Small Vision Model
Train a binary normal/abnormal classifier on the public CheXpert or NIH ChestX-ray14 dataset. Use temperature scaling to calibrate the output, then define abstention thresholds …
- Image Classification
- Transfer Learning
- Calibration
Applied Machine Learning - CodeSeniorNew
Video Action Recognition for a Retail Loss-Prevention Startup
Use a public action-recognition dataset (UCF101 + a small curated retail-action subset; the latter is provided synthetic or you can label 50 short clips). Fine-tune a small back…
- Video Understanding
- Action Recognition
- Transfer Learning
Computer Vision 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
- 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 - CodeIntermediateNew
Prototype a Computer-Vision QA Tool for a Robotics Manufacturer
As a 4-person team, build: (1) a labeling pipeline on around 2,000 component images (Label Studio is fine); (2) a transfer-learned classifier or a small segmentation model that …
- Computer Vision
- Transfer Learning
- Model Deployment
AI Software Engineering Group Project - CodeBeginnerNew
Build a Face-Anonymization Tool for a Civic-Tech Newsroom
Use a pretrained face detector (RetinaFace or YOLOv8-face is fine). Build a Python tool with a Gradio or Streamlit UI that: (1) detects faces in an uploaded photo, (2) shows det…
- Object Detection
- Image Processing
- Opencv
Open coursework - 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
- 3d Object Detection
- Perception
Open coursework - Browse challenges
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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.
- CodeBeginnerNew
Build a Crop-Disease Classifier for a Smallholder Agritech Startup
You receive a curated 22,000-image cassava-disease dataset across 5 classes (4 diseases + healthy) plus a labeled 1,200-image held-out test set. Train a CNN classifier (start wi…
- Image Classification
- Cnn Architectures
- Transfer Learning
Deep Learning for Computer Vision - CodeFoundationalNew
Edge Detection Pipeline for a Manufacturing QA Camera
Use a small provided dataset of around 200 part images under 3 lighting conditions. Build a classical pipeline using OpenCV: grayscale + adaptive thresholding + Canny edge detec…
- Image Processing
- Edge Detection
- Opencv
Computer Vision (Undergraduate) - ResearchBeginnerNew
Drug-Repurposing Candidate Screen with Embedding Similarity
You receive (1) a list of 15 known therapeutic candidates (SMILES + ChEMBL identifiers) for a single rare disease, (2) a database of about 4,500 marketed drugs (SMILES + ATC cod…
- Molecular Embeddings
- Similarity Search
- Transfer Learning
Machine Learning for Healthcare and Biomedicine - ResearchSeniorNew
Plan a Parameter-Efficient Fine-Tuning Strategy for a Big-Tech AI Lab
You will produce (1) a 6-page survey of four PEFT methods (LoRA, adapters, prefix tuning, IA3) with their strengths, weaknesses, and parameter footprints, (2) a one-page decisio…
- Parameter Efficient Fine Tuning
- Transfer Learning
- Fine Tuning
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
Calibrate a Multi-Camera Rig for Warehouse Robotics
You will design and prototype a calibration workflow using a printed ChArUco board (a chessboard with embedded ArUco markers). You receive a sample dataset of 200 raw frames per…
- Camera Calibration
- Multi View Geometry
- Opencv
3D Vision and Multi-View Geometry - CodeIntermediateNew
Scene-Graph Generation for Retail Shelf Audits
You receive 1,500 labeled shelf photos (anonymized product crops, bounding boxes, and ~12 relation types). Build a pipeline that, for a new shelf photo, outputs (a) detected pro…
- Scene Graph Generation
- Object Detection
- Relation Prediction
Open coursework - 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 - CodeBeginnerNew
Semantic Segmentation for a Solar-Panel Inspection Drone
Use a publicly-available solar-panel dataset (or the PV-Defect-Detection dataset). Fine-tune a small U-Net or SegFormer-tiny on panel/no-panel pixel-level segmentation. Evaluate…
- Semantic Segmentation
- Cnn
- Transfer Learning
Open coursework - ResearchSeniorNew
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…
- Self Supervised Learning
- Vision Transformers
- Pytorch
Advanced Deep Learning - AnalysisBeginnerNew
Sales Performance Analysis for a 40-Person SaaS Scale-Up
You will receive a dataset containing 500+ sales opportunities with fields like deal value, stage, source, close date, and account size. Your challenge is to design a data mart …
- Data Warehousing
- Etl
- Olap
Open coursework - CodeIntermediateNew
Few-Shot Defect Classifier for a Fast-Onboarding Industrial AI Vendor
You receive a multi-customer defect dataset (8 historical customers, 4-6 defect classes each). Treat 6 customers as the meta-training set and 2 as the held-out 'new customer' sc…
- Meta Learning
- Few Shot Learning
- Prototypical Networks
Open coursework - StrategyBeginnerNew
Revamping Loyalty for a Mexico City D2C Cosmetics Brand
You are hired as a marketing analyst. Analyze Brillo Natural's existing customer data (provided in a simulated dataset) to identify purchase patterns and decision triggers. Prop…
- Consumer Psychology
- Segmentation
- Loyalty Program Design
Open coursework - AnalysisIntermediateNew
Detect Defects on a Production Line for a Tier-1 Auto Supplier
You receive 12,000 labelled grayscale part images (8,000 good, 4,000 defective across 6 defect types) at 2048x2048. Build a pipeline that does classical preprocessing (illuminat…
- Defect Detection
- Image Classification
- Image Preprocessing
Open coursework - StrategyIntermediateNew
Redesign TaskFlow's Pricing to Win Enterprise Without Losing Small Businesses
Working only from the materials provided to you — the customer accounts and usage dataset (taskflow-accounts-usage), the current pricing and packaging brief (taskflow-pricing-br…
- Pricing Strategy
- Segmentation
- Financial Analysis
Open coursework - CodeBeginnerNew
Team Practicum: Build a Crop-Disease Classifier with a Field Partner
You receive a labeled dataset of about 8,000 phone photos plus around 1,200 unlabeled photos from a held-out county. Audit and clean the labels (expect 5-10% noise), train a Mob…
- Transfer Learning
- Pytorch
- Model Evaluation
Open coursework - CodeIntermediateNew
De-Identify Patient Images for a Pharma Research Pipeline
You receive 500 internal benchmark images (already cleared for use), each labelled with bounding boxes around face/tattoo/jewelry regions. Build a pipeline that detects these re…
- Image De Identification
- Object Detection
- Privacy Preserving Vision
Image Processing and Computational Imaging
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.