Module · Beginner
Image Fundamentals
Images as numbers, convolution as a sliding weighted sum, and why a CNN learns its own filters.
- 3 lessons
- 48 min
- 4 simulations
Included in Computer Vision with Deep Learning· $9
Computer Vision in Production
Models on edge and mobile devices, real-time camera latency, and a capstone project.
- Level
- Intermediate
- Lessons
- 2
- Total time
- 1h 16m
- Simulations
- 2
Included in Computer Vision with Deep Learning · $9
Tools you'll use
Python
PyTorch
OpenCV
Skills
- Edge deployment
- Model optimisation
What you will be able to do
- Run a vision model within a real-time latency budget
Before you start
A suggestion, never a lock — you can start here.
- object-detection
Modules that help first
Syllabus
2 lessons · 1h 16mEvery lesson's title and summary is public. The lessons themselves open once you own the track.
Every lesson in Computer Vision with Deep LearningEdge and Mobile Deployment
16 minSmall models, quantisation and runtimes for phones and cameras.
Included with the track SimulationCapstone: a Vision System
1hFrom an annotated dataset to a running, evaluated detector.
Included with the track Simulation
Lifetime access
$9More in Computer Vision with Deep Learning
Module · Intermediate
Image Classification with CNNs
Building a CNN in PyTorch, transfer learning from pretrained models, and evaluating a classifier honestly.
- 3 lessons
- 56 min
- 3 simulations
Included in Computer Vision with Deep Learning· $9
Module · Intermediate
Object Detection
Bounding boxes, IoU, one-stage detectors like YOLO, and how to read mAP.
- 3 lessons
- 53 min
- 3 simulations
Included in Computer Vision with Deep Learning· $9
Module · Intermediate
Image Segmentation
Classification per pixel: semantic and instance segmentation, U-Net, and general segmentation models.
- 3 lessons
- 46 min
- 2 simulations
Included in Computer Vision with Deep Learning· $9