•Become a Master in Image Processing and Computer Vision 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.
•(Note, we also provide you PDFs and Jupyter Notebooks in case you need them)
•With over 105 lectures and more than 12.5 hours of video this comprehensive course leaves no stone unturned in teaching you Image Processing and Computer Vision with Python 3, NumPy, matplotlib, and OpenCV!
•This course will teach you Image Processing and Computer Vision 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 OpenCV installed on your Windows computer and Raspberry Pi.
•We cover a wide variety of topics, including:
•Basics of Scientific Python Ecosystem
•Basics of OpenCV
•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 of Matplotlib
•Image Processing with NumPy and Matplotlib
•Installation of OpenCV on Windows and RPi
•OpenCV and Matplotlib
•OpenCV and webcam on Windows and RPi
•More Arithmetic and Logical Operations
•More Operations on Images
•Thresholding
•Noise and Filters
•Restoration and Quantization
•Histogram
•Morphological Operations and Max RGB Filters
•Contours and its applications
•Additional Projects
•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 Computer Vision and Image Processing with Python 3 in a way that will advance your career and increase your knowledge, all in a fun and practical way!
•Who this course is for:
•Computer Vision and image Processing Professionals
•Data Science Professionals: Data Scientists and Data Engineers
•Robotics and Machine Vision Professionals
•AI and Machine Learning Professionals
•Scientists, Mathematicians, Physicists, and Engineers
•Python Developers and Programmers
•Managers and Business Professionals
•Anyone who wants to learn
•Course Topics Overview
•Please do leave your feedback for this course
•Processing..
•Scientific Python Ecosystem
•Important Web URLs for all the projects in Scientific Python Ecosystem
•What is Digital Image Processing?
•What is Computer Vision?
•Python 3 on Windows
•Python 3 on Installation on Windows
•Verification of Python 3 Environment on Windows
•Python 3 on Raspberry Pi
•What is Raspberry Pi
•Unboxing of RPi 3B+
•Web URLs of softwares for downloads
•Raspbian OS Installation Part 1
•Raspbian OS Installation Part 2
•Install VNC and connect to the Raspberry Pi desktop remotely
•List of Linux commands used in the installation
•Install IDLE3 on Raspberry Pi Raspbian
•Python 3 on Raspberry Pi Raspbian OS
•Python 3 Basics
•Hello World! on Windows Improved
•Hello World! on Raspberry Pi
•Python 3 Scripting vs Interpreter Mode
•A brief Tour of IDLE
•PC vs RPi
•Python Package Index and pip
•Python Package Index and pip explained
•pip on Windows
•pip on Raspberry Pi
•Install NumPy and matplotlib on Windows and Raspberry Pi
•Install NumPy and matplotlib on Windows
•Install NumPy and matplotlib on Raspberry Pi
•Jupyter Notebook
•Jupyter and IPython improved
•Jupyter Installation on Windows
•Jupyter Installation on Raspberry Pi
•PuTTY
•Connecting to Remote Jupyter Notebook
•A brief tour of Jupyter
•Getting Started with NumPy
•Introduction to NumPy
•Ndarray, Indexing, and Slicing improved
•Ndarrays Properties
•NumPy Constants
•NumPy DataTypes
•Creation of Arrays and Matplotlib
•Ones and Zeros
•Matrices
•Matplotlib
•Numerical Value Ranges and Visualizations
•Random Sampling
•Plotting in Details
•Single Line Plots
•Multiline Plots
•Grid, Axes, and Labels
•Color and Line Markers
•Image Processing with Python, NumPy, and Matplotlib
•Image Datasets
•Pillow Installation on Windows and RPi
•Reading, Displaying, and Saving images
•NumPy for Images
•Image Statistics
•Image Masks
•Image Channels
•Arithmetic Operations
•Logical Operations
•Histograms with NumPy and Matplotlib
•Getting Started with OpenCV
•Installation and Verification
•Read, Display, and Save images
•Draw Geometric Shapes
•Trackbar and Color Palette Application
•Drawing App
•Matplotlib and Colorspace Conversion
•Work with Webcam
•Capture a still
•Capture a Live Video
•Set the resolution
•Video Recording
•Show FPS
•Video Player
•Object Tracking by Color
•Operations on Images
•Division and Multiplication
•Image Blending
•Image Transition
•Image Transition App
•Logical Bitwise Operations
•add() function
•Transformations
•Affine Transformations Part 1
•Affine Transformations Part 2
•Affine Transformations Part 3
•Perspective Transforms
•Otsu
•Adaptive/Local Thresholding
•Thresholding Live Webcam feed
•Image Filtering
•Noise Types
•Kernels and Convolution
•Low Pass Filters
•Salt and pepper noise and Median Blur Filter
•High Pass Filters
•Canny Edge Detection
•Canny on Live Webcam
•Advanced Concepts in OpenCV
•Image Quantization with K Means Clustering
•Image Histogram
•Histogram Equalization
•Morphological Operations
•Contour
•Max RGB Filter
•KMeans Revisited
•Harris Corner Detection
•Check Video File Resolution
•Downloadable Code Files
•