10 Best Computer Vision Courses and Certifications Online 2023

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There are countless online courses and classes that will help you improve your Computer Vision skills and earn your Computer Vision certificate.

In this article, our experts have actually assembled a curated list of the 10 Best of the Best Computer Vision courses, tutorials, training programs, classes and certifications that are available online right now.

We have included only those courses that fulfill our high-quality standards. We have put a great deal of time and effort into collecting these all for you. These courses are suitable for all levels, beginners, intermediate learners, and experts.

Here’s a look at these courses and what they have to offer for you!

10 Best Computer Vision Courses and Certifications Online

Course Name	Enrolled Students (Count)	Reviews (count)
1. Convolutional Neural Networks in Python: CNN Computer Vision Our Best Pick	117856+	1123+
2. “Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs”	45199+	6293+
3. Python for Computer Vision with OpenCV and Deep Learning	44712+	8367+
4. Computer Vision Masterclass	27979+	522+
5. Deep Learning :Adv. Computer Vision (object detection+more!)	23888+	1016+
6. Master Computer Vision™ OpenCV4 in Python with Deep Learning	20673+	3544+
7. “Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs”	13545+	2050+
8. Autonomous Cars: Deep Learning and Computer Vision in Python	9440+	1016+
9. Learn Computer Vision and Image Processing in LabVIEW	4619+	353+
10. “Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4”	4533+	382+

1. Convolutional Neural Networks in Python: CNN Computer Vision by Start-Tech Academy Udemy Course Our Best Pick

Python for Computer Vision & Image Recognition – Deep Learning Convolutional Neural Network (CNN) – Keras & TensorFlow 2

As of right now, more than 117856+ people have enrolled in this course and there are over 1123+ reviews.

Course Content

Introduction
Setting up Python and Jupyter Notebook
Single Cells – Perceptron and Sigmoid Neuron
Neural Networks – Stacking cells to create network
Important concepts: Common Interview questions
Standard Model Parameters
Tensorflow and Keras
Python – Dataset for classification problem
Python – Building and training the Model
Python – Solving a Regression problem using ANN
Complex ANN Architectures using Functional API
Saving and Restoring Models
Hyperparameter Tuning
CNN – Basics
Creating CNN model in Python
Analyzing impact of Pooling layer
Project : Creating CNN model from scratch
Project : Data Augmentation for avoiding overfitting
Transfer Learning : Basics
Transfer Learning in Python
Congratulations & about your certificate

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2. “Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs” by “Hadelin de Ponteves, Kirill Eremenko, Ligency I Team, Ligency Team” Udemy Course

Become a Wizard of all the latest Computer Vision tools that exist out there. Detect anything and create powerful apps.

As of right now, more than 45199+ people have enrolled in this course and there are over 6293+ reviews.

Course Content

Introduction
Module 1 – Face Detection Intuition
Module 1 – Face Detection with OpenCV
Homework Challenge – Build a Happiness Detector
Module 2 – Object Detection Intuition
Module 2 – Object Detection with SSD
Homework Challenge – Detect Epic Horses galloping in Monument Valley
Module 3 – Generative Adversarial Networks (GANs) Intuition
Module 3 – Image Creation with GANs
Annex 1: Artificial Neural Networks
Annex 2: Convolutional Neural Networks
Bonus Lectures

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3. Python for Computer Vision with OpenCV and Deep Learning by Jose Portilla Udemy Course

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

As of right now, more than 44712+ people have enrolled in this course and there are over 8367+ reviews.

Course Content

Course Overview and Introduction
NumPy and Image Basics
Image Basics with OpenCV
Image Processing
Video Basics with Python and OpenCV
Object Detection with OpenCV and Python
Object Tracking
Deep Learning for Computer Vision
Capstone Project
BONUS SECTION: THANK YOU!

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4. Computer Vision Masterclass by “Jones Granatyr, Ligency I Team, Ligency Team, Gabriel Alves, IA Expert Academy” Udemy Course

Learn in practice everything you need to know about Computer Vision! Build projects step by step using Python!

As of right now, more than 27979+ people have enrolled in this course and there are over 522+ reviews.

Course Content

Introduction
Face detection
Face recognition
Object tracking
Neural networks for image classification
Convolutional neural networks for image classification
Transfer learning and fine tuning
Neural networks for classification of emotions
Autoencoders
Object detection with YOLO
Recognition of gestures and actions
Deep dream
Style transfer
GANs (Generative adversarial networks)
Image segmentation
Final remarks

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5. Deep Learning :Adv. Computer Vision (object detection+more!) by Jay Bhatt Udemy Course

“Transfer Learning, TensorFlow Object detection, Classification, Yolo object detection, real time projects much more..!!”

As of right now, more than 23888+ people have enrolled in this course and there are over 1016+ reviews.

Course Content

Introduction
Starting with google colab and Gdrive
Creating Your First Transfer learning model
Introduction to State of Art models
Model Explainability and feature-maps
Introduction to object detection with Yolo
Object Detection with TensorFlow
Cv2 experiments
Bonus Theory lectures and Exercises
bonus

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6. Master Computer Vision™ OpenCV4 in Python with Deep Learning by Rajeev D. Ratan Udemy Course

“Master OpenCV4 like a pro while learning Dlib, Deep Learning Computer Vision (Keras, TensorFlow & Caffe) + 21 Projects!”

As of right now, more than 20673+ people have enrolled in this course and there are over 3544+ reviews.

Course Content

“Course Introduction and Setup
Basics of Computer Vision and OpenCV
Image Manipulations & Processing
Image Segmentation & Contours
Object Detection in OpenCV
Object Detection – Build a Face, People and Car/Vehicle Detectors
Augmented Reality (AR) – Facial Landmark Identification (Face Swaps)
Simple Machine Learning using OpenCV
Object Tracking & Motion Analysis
Computational Photography & Make a License Plate Reader
Conclusion
BONUS – Deep Learning Computer Vision 1 – Setup a Deep Learning Virtual Machine
BONUS – Deep Learning Computer Vision 2 – Introduction to Neural Networks
BONUS – Deep Learning Computer Vision 3 – Convolutional Neural Networks (CNNs)
BONUS – Deep Learning Computer Vision 4 – Build CNNs in Python using Keras
BONUS – Deep Learning Computer Vision 5 – Build a Cats vs Dogs Classifier
BONUS – Build a Credit Card Number Reader
BONUS – Neural Style Transfer with OpenCV
BONUS – Object Detection – Use SSDs (Single Shot Detector) for Detecting Objects
BONUS – Colorize Black and White Images”

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7. “Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs” by Rajeev D. Ratan Udemy Course

2020 Update with TensorFlow 2.0 Support. Become a Pro at Deep Learning Computer Vision! Includes 20+ Real World Projects

As of right now, more than 13545+ people have enrolled in this course and there are over 2050+ reviews.

Course Content

“Introduction
Intro to Computer Vision & Deep Learning
Installation Guide
Handwriting Recognition
OpenCV Tutorial – Learn Classic Computer Vision & Face Detection (OPTIONAL)
Neural Networks Explained
Convolutional Neural Networks (CNNs) Explained
Build CNNs in Python using Keras
What CNNs ‘see’ – Filter Visualizations, Heatmaps and Salience Maps
Data Augmentation: Cats vs Dogs
Assessing Model Performance
Optimizers, Learning Rates & Callbacks with Fruit Classification
Batch Normalization & LeNet, AlexNet: Clothing Classifier
Advanced Image Classiers – ImageNet in Keras (VGG16/19, InceptionV3, ResNet50)
Transfer Learning: Build a Flower & Monkey Breed Classifier
Design Your Own CNN – LittleVGG: A Simpsons Classifier
Advanced Activation Functions & Initializations
Facial Applications – Emotion, Age & Gender Recognition
Medical Imaging – Image Segmentation with U-Net
Principles of Object Detection
TensorFlow Object Detection API
Object Detection with YOLO & Darkflow: Build a London Underground Sign Detector
DeepDream & Neural Style Transfers: Make AI Generated Art
Generative Adversarial Networks (GANs): Simulate Aging Faces
Face Recognition with VGGFace
The Computer Vision World
BONUS – Build a Credit Card Number Reader
BONUS – Use Cloud GPUs on PaperSpace
BONUS – Create a Computer Vision API & Web App Using Flask and AWS”

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8. Autonomous Cars: Deep Learning and Computer Vision in Python by “Sundog Education by Frank Kane, Frank Kane, Dr. Ryan Ahmed, Ph.D., MBA, Mitchell Bouchard, Sundog Education Team” Udemy Course

“Learn OpenCV, Keras, object and lane detection, and traffic sign classification for self-driving cars”

As of right now, more than 9440+ people have enrolled in this course and there are over 1016+ reviews.

Course Content

Environment Setup and Installation
Introduction to Self-Driving Cars
Python Crash Course [Optional]Computer Vision Basics: Part 1
Computer Vision Basics: Part 2
Computer Vision Basics: Part 3
Machine Learning: Part 1
Machine Learning: Part 2
Artificial Neural Networks
Deep Learning and Tensorflow: Part 1
Deep Learning and Tensorflow: Part 2
Wrapping Up

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9. Learn Computer Vision and Image Processing in LabVIEW by Augmented Startups Udemy Course

Learn Computer Vision and Image Processing From Scratch in LabVIEW and build 9 Vision-based Apps

As of right now, more than 4619+ people have enrolled in this course and there are over 353+ reviews.

Course Content

Basics of LabVIEW Vision Development Module
Color Processing
Basic Feature Detection
Lines and Edges
Advanced Feature Detection
Conclusion and Bonus Section

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10. “Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4” by Rajeev D. Ratan Udemy Course

“Using Python Learn OpenCV4, CNNs, Detectron2, YOLOv5, GANs, Tracking, Segmentation, Face Recognition & Siamese Networks”

As of right now, more than 4533+ people have enrolled in this course and there are over 382+ reviews.

Course Content

“Introduction
Download Code and Setup Colab
OpenCV – Image Operations
OpenCV – Image Segmentation
OpenCV – Haar Cascade Classifiers
OpenCV – Image Analysis and Transformation
OpenCV – Motion and Object Tracking
OpenCV – Facial Landmark Detection & Face Swaps
OpenCV Projects
OpenCV – Working With Video
Deep Learning in Computer Vision Introduction
Building CNNs in PyTorch
Building CNNs in TensorFlow with Keras
Assessing Model Performance
Improving Models and Advanced CNN Design
Visualizing What CNN’s Learn
Advamced Convolutional Neural Networks
Building and Loading Advanced CNN Archiectures and Rank-N Accuracy
Using Callbacks in Keras and PyTorch
PyTorch Lightning
Transfer Learning and Fine Tuning
Google DeepStream and Neural Style Transfer
Autoencoders
Generative Adversarial Networks (GANs)
Siamese Network
Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning
Object Detection
Modern Object Detectors – YOLO, EfficientDet, Detectron2
Gun Detector – Scaled-YoloV4
Mask Detector TFODAPI MobileNetV2_SSD
Sign Language Detector TFODAPI EfficentDet
Pothole Detector – TinyYOLOv4
Mushroom Detector Detectron2
Website Region Detector YOLOv4 Darknet
Drone Maritime Detector R-CNN
Chess Piece YOLOv3
Bloodcell Detector YOLOv5
Hard Hat Detector EfficentDet
Plant Doctor Detector YOLOv5
Deep Segmentation – U-Net, SegNet, DeeplabV3 and Mask R-CNN
Body Pose Estimation
Tracking with DeepSORT
Deep Fakes
Vision Transformers – ViTs
BiT BigTransfer Classifier Keras
Depth Estimation
Image Similarity using Metric Learning
Image Captioning with Keras
Video Classification usign CNN+RNN
Video Classification with Transformers
Point Cloud Classification PointNet
Point Cloud Segmentation Using PointNet
Medical Project – X-Ray Pneumonia Prediction
Medical Project – 3D CT Scan Classification
Low Light Image Enhancement MIRNet
Deploy your CV App using Flask RestFUL API & Web App
OCR Captcha Cracker”

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Here are some frequently asked questions about learning Computer Vision

How Long Does It Take to Learn Computer Vision?

The answer to the question “How long does it ttake to learn Computer Vision” is … it depends. Everybody has different requirements, and everybody is operating in different scenarios, so the answer for a single person might be completely different than for another person.

Consider these questions: What are you attempting to Learn Computer Vision for? Where is your beginning point? Are you a newbie or do you have experience with Computer Vision? How much can you practice? 1 hour daily? 40 hours per week? Check out this course about Computer Vision.

Is Computer Vision Easy Or Hard to Learn?

No, learning Computer Vision isn’t hard for many people. Check this course on how to Learn Computer Vision in no time!

How to Learn Computer Vision Fast?

The fastest method to Learn Computer Vision is to first get this Computer Vision course, then practice whatever you learn whenever you can. Even if its simply 15 minutes a day of practice. Consistency is key.

Where to Learn Computer Vision?

If you want to explore and learn Computer Vision, then Udemy provides you the best platform to learn the Computer Vision. Check this course on how to Learn Computer Vision in no time!

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