Course Information
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Course Overview
Become an expert in Image Processing in Python 3: Learn Scikit-image and OpenCV with NumPy, Matplotlib, and Jupyter
Become a Master in Image Processing with Python 3 and acquire employers' one of the most requested skills of 21st Century! An expert level image processing and computer vision professional can earn minimum $100000 (that's five zeros after 1) in today's economy.
This is the most comprehensive, yet straight-forward course for the Image Processing and Computer Vision with Python 3 on Udemy! Whether you have never worked with Image Processing before, already know basics of Python, or want to learn the advanced features of scikit-image with Python 3, this course is for you! In this course we will teach you Scikit-image with Python 3, Jupyter, NumPy, and Matplotlib.
(Note, we also provide you PDFs and Jupyter Notebooks in case you need them)
With over 100 lectures and more than 12 hours of video this comprehensive course leaves no stone unturned in teaching you Image Processing with Python 3!
This course will teach you Image Processing in a very practical manner, with every lecture comes a programming video and a corresponding Jupyter notebook that has Python 3 code! Learn in whatever manner is the best for you!
We will start by helping you get Python3, NumPy, matplotlib, Jupyter, and Scikit-learn installed on your Windows computer and Raspberry Pi.
We cover a wide variety of topics, including:
Basics of Scientific Python Ecosystem
Basics of Digital Image Processing
Basics of NumPy and Matplotlib
Installation of Python 3 on Windows
Setting up Raspberry Pi
Tour of Python 3 environment on Raspberry Pi
Jupyter installation and basics
NumPy Ndarrays
Array Creation Routines
Basic Visualization with Matplotlib
Ndarray Manipulation
Random Array Generation
Bitwise Operations
Statistical Functions
Basics Image Processing with NumPy and Matplotlib
Installation of Scikit-image
Reading and Displaying Images
Shapes
Transformations on images
Histogram Equalization
Thresholding
Filtering
Morphology
Improving Images
Feature Detection
Segmentation
Miscellaneous operations on images
and much more.....
You will get lifetime access to over 100 lectures plus corresponding PDFs, Image Datasets, and the Jupyter notebooks for the lectures!
So what are you waiting for? Learn Image Processing with Python 3 in a way that will advance your career and increase your knowledge, all in a fun and practical way!
Course Content
- 26 section(s)
- 99 lecture(s)
- Section 1 Introduction
- Section 2 Installation of Python 3 on a Windows Computer
- Section 3 Python 3 on Raspberry Pi
- Section 4 Basics of Python 3
- Section 5 Python Package Index and pip
- Section 6 Installing NumPy and Matplotlib
- Section 7 Jupyter Notebook for Scientific Computing
- Section 8 Introduction to NumPy
- Section 9 Creating and visualizing NumPy Ndarrays
- Section 10 Random Sampling
- Section 11 Ndarray Manipulation Routines
- Section 12 Bitwise Operations
- Section 13 Statistical Functions in NumPy
- Section 14 NumPy and Matplotlib for Image Processing
- Section 15 scikit-image installation on Windows and Raspberry Pi
- Section 16 Getting Started with scikit-image
- Section 17 Transformations, Thresholding, and Histogram Equalization
- Section 18 Filters in scikit-image
- Section 19 Morphology and Image Restoration
- Section 20 Noise and Noise Reduction
- Section 21 Feature Detection
- Section 22 Segmentation
- Section 23 Advanced Operations on Image
- Section 24 More Scikit-image
- Section 25 Downloadable Contents
- Section 26 BONUS SECTION
What You’ll Learn
- Understand the concepts in Image Processing
- Understand the Scientific Python Ecosystem
- Image processing and visualization using NumPy and Matplotlib
- Image Processing with scikit-image
Skills covered in this course
Reviews
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UUmang Mandilwar
It was a very good experience of learning some new features and algorithms related to image processing and I would also recommend it to my friends. Only thing I wanted was more explanation on vast topics like feature detection and morphology and also transformations but overall the lectures were to the point and holding the base of the course.
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RRobert Perliński
A lot of algorithms but not much explanation how they work and when to use them. Sometimes Author do not understand what is going in his code, but generally one can by familiar with image processing in python so, I have learned something. English language was hard to hear, at least at the beginning before I get used to "English" speaker.
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NNoha El-Yamany
I am very disappointed. One would have bought a book and studied on his/her own better. The instructor is just talking and typing code without an motivation. He clearly lacks solid understanding of image processing, and he does not explain the content well.
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JJames Marks
Little to no explanation of what the purpose of each process is. Much appears taken straight from module documentation