پیش نیازها:
این دوره برای چه کسی است؟
- توسعه دهندگان مبتدی پایتون که در مورد علم داده کنجکاو هستند

در ادامه با برخی از سرفصل های درسی این مجموعه آموزش آشنا می شویم :
Introduction
Make images come alive with scikit-image
RGB to grayscale
NumPy for images
Flipping out
Histograms
Getting started with thresholding
Apply global thresholding
When the background isn't that obvious
Trying other methods
Apply thresholding
Filters, Contrast, Transformation and Morphology
Jump into filtering
Edge detection
Blurring to reduce noise
Contrast enhancement
Aerial image
Let's add some impact and contrast
Transformations
Enlarging images
Proportionally resizing
Morphology
Handwritten letters
Improving thresholded image
Image restoration, Noise, Segmentation and Contours
Image restoration
Removing logos
Noise
Let's make some noise!
Reducing noise
Reducing noise while preserving edges
Superpixels & segmentation
Superpixel segmentation
Finding contours
Contouring shapes
Count the dots in a dice's image
Advanced Operations, Detecting Faces and Features
Finding the edges with Canny
Edges
Right around the corner
Perspective
Face detection
Is someone there?
Multiple faces
Segmentation and face detection
Real-world applications
Privacy protection
Help Sally restore her graduation photo