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Python for Computer Vision with OpenCV and Deep Learning (Udemy.com)

Learn the latest techniques in computer vision with Python , OpenCV , and Deep Learning!

Created by: Jose Portilla

Last updated March 2021

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What you will learn

  • Understand basics of NumPy
  • Manipulate and open Images with NumPy
  • Use OpenCV to work with image files
  • Use Python and OpenCV to draw shapes on images and videos
  • Perform image manipulation with OpenCV, including smoothing, blurring, thresholding, and morphological operations.
  • Create Color Histograms with OpenCV
  • Open and Stream video with Python and OpenCV
  • Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python
  • Create Face Detection Software
  • Segment Images with the Watershed Algorithm
  • Track Objects in Video
  • Use Python and Deep Learning to build image classifiers
  • Work with Tensorflow, Keras, and Python to train on your own custom images.

How it compares

Against the other 388 rated Udemy courses in Python on CourseDuck:

  • Rating4.6 out of 5higher than 70% of them
  • Reviews13,399#32 of 389 by number of reviews
  • Length14.1 hourslonger than 64% of them
  • Last updatedMarch 2021earlier than 68% of them

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Course Description

Welcome to the ultimate online course on Python for Computer Vision!

This course is your best resource for learning how to use the Python programming language for Computer Vision.

We'll be exploring how to use Python and the OpenCV (Open Computer Vision) library to analyze images and video data.

The most popular platforms in the world are generating never before seen amounts of image and video data. Every 60 seconds users upload more than 300 hours of video to Youtube, Netflix subscribers stream over 80,000 hours of video, and Instagram users like over 2 million photos! Now more than ever its necessary for developers to gain the necessary skills to work with image and video data using computer vision.

Computer vision allows us to analyze and leverage image and video data, with applications in a variety of industries, including self-driving cars, social network apps, medical diagnostics, and many more.

As the fastest growing language in popularity, Python is well suited to leverage the power of existing computer vision libraries to learn from all this image and video data.

In this course we'll teach you everything you need to know to become an expert in computer vision! This $20 billion dollar industry will be one of the most important job markets in the years to come.

We'll start the course by learning about numerical processing with the NumPy library and how to open and manipulate images with NumPy. Then will move on to using the OpenCV library to open and work with image basics. Then we'll start to understand how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more.

Then we'll move on to understanding video basics with OpenCV, including working with streaming video from a webcam.  Afterwards we'll learn about direct video topics, such as optical flow and object detection. Including face detection and object tracking.

Then we'll move on to an entire section of the course devoted to the latest deep learning topics, including image recognition and custom image classifications. We'll even cover the latest deep learning networks, including the YOLO (you only look once) deep learning network.

This course covers all this and more, including the following topics:

  • NumPy

  • Images with NumPy

  • Image and Video Basics with NumPy

  • Color Mappings

  • Blending and Pasting Images

  • Image Thresholding

  • Blurring and Smoothing

  • Morphological Operators

  • Gradients

  • Histograms

  • Streaming video with OpenCV

  • Object Detection

  • Template Matching

  • Corner, Edge, and Grid Detection

  • Contour Detection

  • Feature Matching

  • WaterShed Algorithm

  • Face Detection

  • Object Tracking

  • Optical Flow

  • Deep Learning with Keras

  • Keras and Convolutional Networks

  • Customized Deep Learning Networks

  • State of the Art YOLO Networks

  • and much more!

Feel free to message me on Udemy if you have any questions about the course!

Thanks for checking out the course page, and I hope to see you inside!

Jose

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Instructor Details

Jose Portilla

Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, SalesForce, Starbucks, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.

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Reviews

4.6

13,399 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Marco Aurelio Nuño-Maganda on 2/13/2026

This course is a great hands-on introduction to computer vision. It explains concepts clearly and quickly moves into practical examples, making it easy to see how OpenCV and deep learning are used in real applications. It’s a very engaging and useful as a tool to be used in a classroom.

By Wang Leong Wong on 1/14/2026

The first 8 sections are fine. The instructor shows the most interesting part (to general people) of open CV. Section 9 demonstrates a common problem of computer vision application -- there are many steps and you (as readers of other's codes) are not 100% sure intermediate results of these steps. Even if you were the original author, you would forget most details of the steps after some years.

By Chérise Tomsjansen on 10/20/2025

This course is great for all levels of Python knowledge. It starts with the basics and gradually increases in difficulty, covering more advanced topics in deep learning. Even if you don't understand the material, the code is provided so you can review it at your own pace. The teacher doesn't make you feel stupid, which is great if you want to learn efficiently.

By Başak Heybeli on 9/11/2025

The course is great. I am a computer science student and only have had experience in C and Python, so I would call myself a beginner-intermediate in coding. However I pretty much understood everything througout the course. The only problem was that I felt like it became a bit too complex in Deep Learning part and I had hard time understanding the material. It only made me feel like I needed to memorize the code. Other than that the course is great! The instructor is amazing and very well spoken! He regularly encourages to learn and makes the learning process lighter. I would definitely recommend this course! :)

By Neeraj on 1/19/2022

I am giving 4 starts not 5 because of these 2 points 1. Sometimes you didn't explain complicated things in details. 2. Secondly for your next course please don't build the whole project in one go, do some code and show us the output so we can relate the things. In Capstone Project, you built the entire project in one go and then showed us.

By Jonah Sokipriala on 9/25/2020

the delivery in this course is one of the best have seen so far, the use of the assessment is really nice this helps reinforce what you have learnt in any section, would encourage everyone not to skip the assessment. after going through this course I had to buy another course from jose

By Okan Zagor Akkoyun on 7/18/2020

It was a lot of fun and the presentation was very professional although he was very cold to questions and overall indifferent to certain minor problems that were noticed by the audience after the release of this course. For example, he would accidentally skip a piece of code (confusing me and probably everyone else), and he wouldn't really make up for it. The quality was still the best and the presentation was still the most professional among all of my Udemy courses though.

By Miroslav Radojević on 5/20/2020

Course completely fulfills the expectations and provides with solid knowledge basis to kick-off with practicing python in computer vision in case one has basic familiarity with the field. There is a brief but effective intro to convolutional neural nets and deep learning which is also very handy.

By Kiran Kumar Reddy Y on 2/5/2020

Please provide the text for what you speak, I am not able to understand clearly what you are speaking, " you are speaking very fast... it is very hard to understand for Asian people". So naturally we are getting irritation. So please look at these two things. The course content and remaining all things are Superb... Thank for providing good content.

By Ali Ihsan Elmas on 12/30/2019

I've just finished the half of the course and I'm using C# instead of python for examples. So, If you don't have python experience before don't be afraid as long as you got experience with some other programming languages you will be able to understand the topics. So far the course is great! Better than what I expected! Here are some things worth mentioning about the course: - Provides clear and well prepared explanations, - There are exercises that cover all the things you learn during the section with solutions at the end of each section, - It's obvious that the lecturer has a strong grasp of the topics. I strongly recommend this course!

Showing all 10 reviews on CourseDuck

Read all 13,399 reviews on Udemy

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Quality Score

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Overall Score : 92 / 100