HOT
blank

Complete Python Image Processing Masterclass

Development

Rating4.5
Enroll Now

Complete Python Image Processing Masterclass, available at $54.99, has an average rating of 4.5, with 100 lectures, based on 255 reviews, and has 2304 subscribers.

You will learn about Understand the concepts in Image Processing Understand the Scientific Python Ecosystem Image processing and visualization using NumPy and Matplotlib Image Processing with scikit-image This course is ideal for individuals who are Computer Vision and Image/Signal Processing Professionals or Digital Imaging Professionals or AI and Machine Learning Professionals or Robotics Professionals or Data Science Professionals or Scientists or Mathematicians or Physicists or Anyone with zeal and enthusiasm to learn It is particularly useful for Computer Vision and Image/Signal Processing Professionals or Digital Imaging Professionals or AI and Machine Learning Professionals or Robotics Professionals or Data Science Professionals or Scientists or Mathematicians or Physicists or Anyone with zeal and enthusiasm to learn.

Enroll now: Complete Python Image Processing Masterclass

Summary

Title: Complete Python Image Processing Masterclass

Price: $54.99

Average Rating: 4.5

Number of Lectures: 100

Number of Published Lectures: 99

Number of Curriculum Items: 100

Number of Published Curriculum Objects: 99

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

  • Computer Vision and Image/Signal Processing Professionals
  • Digital Imaging Professionals
  • AI and Machine Learning Professionals
  • Robotics Professionals
  • Data Science Professionals
  • Scientists
  • Mathematicians
  • Physicists
  • Anyone with zeal and enthusiasm to learn

Target Audiences

  • Computer Vision and Image/Signal Processing Professionals
  • Digital Imaging Professionals
  • AI and Machine Learning Professionals
  • Robotics Professionals
  • Data Science Professionals
  • Scientists
  • Mathematicians
  • Physicists
  • Anyone with zeal and enthusiasm to learn

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 Curriculum

Chapter 1: Introduction

Lecture 1: Objectives, Prerequisites, and Audience

Lecture 2: Course Content Walkthrough

Lecture 3: The Scientific Python Ecosystem

Lecture 4: What is Image Processing

Lecture 5: Please do leave your feedback for the course

Lecture 6: What is Computer Vision

Lecture 7: What is scikit-image

Lecture 8: Projects in the Scientific Python Ecosystem

Chapter 2: Installation of Python 3 on a Windows Computer

Lecture 1: Installation of Python 3 on a Windows Computer

Lecture 2: Verify the Python 3 environment on Windows OS

Chapter 3: Python 3 on Raspberry Pi

Lecture 1: What is Raspberry Pi?

Lecture 2: Raspberry Pi OS Setup

Lecture 3: VNC

Lecture 4: Install IDLE3 on Raspberry Pi Raspbian

Lecture 5: Python 3 on Raspberry Pi

Lecture 6: Additional Software for Remote connection

Chapter 4: Basics of Python 3

Lecture 1: Hello World! on Windows

Lecture 2: Hello World! on Raspberry Pi

Lecture 3: Python 3 Interpreter vs Script Mode

Lecture 4: IDLE

Lecture 5: Raspberry Pi vs PC

Chapter 5: Python Package Index and pip

Lecture 1: PyPI and pip

Lecture 2: pip on Windows

Lecture 3: pip on Raspberry Pi

Chapter 6: Installing NumPy and Matplotlib

Lecture 1: Install NumPy and Matplotlib on Windows

Lecture 2: Install NumPy and Matplotlib on Raspberry Pi

Chapter 7: Jupyter Notebook for Scientific Computing

Lecture 1: Jupyter and IPython

Lecture 2: Jupyter Installation on Windows

Lecture 3: Jupyter Installation on Raspberry Pi

Lecture 4: Install PuTTy on Windows

Lecture 5: Connecting to the Remote Jupyter Notebook Server

Lecture 6: A brief tour of Jupyter

Lecture 7: Jupyter Installation and Remote connection commands

Chapter 8: Introduction to NumPy

Lecture 1: What is NumPy

Lecture 2: Ndarrays, Indexing, and slicing

Lecture 3: Ndarray Properties

Lecture 4: NumPy Constants

Lecture 5: NumPy Datatypes

Chapter 9: Creating and visualizing NumPy Ndarrays

Lecture 1: Ones and Zeros

Lecture 2: Matrices

Lecture 3: What is Matplotlib

Lecture 4: Numerical Ranges and Visualization

Chapter 10: Random Sampling

Lecture 1: Generating Ndarrays with Random values

Chapter 11: Ndarray Manipulation Routines

Lecture 1: Ndarray Manipulation Routines

Chapter 12: Bitwise Operations

Lecture 1: Bitwise Operations

Chapter 13: Statistical Functions in NumPy

Lecture 1: Statistical Functions in NumPy

Chapter 14: NumPy and Matplotlib for Image Processing

Lecture 1: Image Datasets for Practice

Lecture 2: Pillow installation on Windows and Raspberry Pi

Lecture 3: Reading Displaying and Saving Images with Matplotlib

Lecture 4: Numpy for Images

Lecture 5: Image Statistics

Lecture 6: Image Masks

Lecture 7: Image Channels

Lecture 8: Arithmetic Operations

Lecture 9: Logical Operations

Lecture 10: Histograms with NumPy and Matplotlib

Chapter 15: scikit-image installation on Windows and Raspberry Pi

Lecture 1: Install SciPy on Windows

Lecture 2: Install SciPy on Raspberry Pi

Lecture 3: scikit-image installation on Windows

Lecture 4: scikit-image installation on Raspberry Pi

Lecture 5: Downloadable Installation Guide

Chapter 16: Getting Started with scikit-image

Lecture 1: Getting Started

Lecture 2: Shapes.. Shapes.. Shapes……

Lecture 3: Color Conversion

Chapter 17: Transformations, Thresholding, and Histogram Equalization

Lecture 1: Thresholding

Lecture 2: Transformations

Lecture 3: Histogram Equalization

Chapter 18: Filters in scikit-image

Lecture 1: Filters – Part 1

Lecture 2: Filters – Part 2

Lecture 3: Filters – Part 3

Chapter 19: Morphology and Image Restoration

Lecture 1: Morphology

Lecture 2: Image Restoration

Chapter 20: Noise and Noise Reduction

Lecture 1: Noise

Lecture 2: Noise Reduction

Chapter 21: Feature Detection

Lecture 1: Canny Edge Detector

Lecture 2: Harris Corner Detection

Chapter 22: Segmentation

Lecture 1: SLIC Segmentation

Lecture 2: Region Boundary based RAGs

Instructors

Rating Distribution

  • 1 stars: 6 votes
  • 2 stars: 13 votes
  • 3 stars: 47 votes
  • 4 stars: 78 votes
  • 5 stars: 111 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

You may also like

Top 10 Ethical AI Courses to Learn in November 2024

Top 10 Game Development Courses to Learn in November 2024

Top 10 Software Testing Courses to Learn in November 2024