8 Best Convolutional Neural Network Resources in 2025

Do you want to know Best Convolutional Neural Network Resources?… If yes, this article is for you. In this article, you will find the 8 Best Convolutional Neural Network Resources.

Now without any further ado, let’s get started-

Best Convolutional Neural Network Resources

Before I discuss the Best Convolutional Neural Network Resources, let’s see, What Convolutional Neural Network(CNN) is.

What is Convolutional Neural Network?

Convolutional Neural Network is an algorithm of Deep Learning. That is used for Image Recognition and Natural Language Processing. Convolutional Neural Network (CNN) takes an image to identify its features and predict it.

Yann Lecun is the father of the Convolutional Neural Network. He is a student of Geoffrey Hilton. Geoffrey Hilton is the father of Artificial Neural networks.

So let’s see how CNN works-

So, this is the basic structure of the Convolutional Neural Network. This input image may be anything, CNN takes this image to perform the operation and then classify it.

Convolutional Neural networks can be used in Sentiment Analysis. That means it can detect that person is happy or sad based on the feature of the images.

This is an emoticon just for a reference, but CNN can identify the emotions of human faces. CNN gives the probability for example it can say 90% is the probability that the person is happy.

Now, let’s see Best Convolutional Neural Network Resources–

1. Intro to Deep Learning with PyTorch– Udacity

Time to Complete- 2 Months

This is a FREE deep learning online course. In this course, you will learn how to train a convolutional network to classify dog breeds from images of dogs. After that, you will learn style transfer and how to build recurrent neural networks with PyTorch.

This course will also cover how to implement a network that learns from Tolstoy’s Anna Karenina to generate new text based on the novel. In the end, you will learn Natural Language Classification and use your network to predict the sentiment of movie reviews.

Who Should Enroll?

• Those who are comfortable with Python and data processing libraries such as NumPy and Matplotlib.

Interested to Enroll?

If yes, then start learning- Intro to Deep Learning with PyTorch

2. Convolutional Neural Networks– deeplearning.ai

Time to Complete- 41 hours

Rating- 4.9/5

In this course, you will understand the basics of Convolutional Neural Networks. And learn the implementation of foundational layers of CNNs (pooling, convolutions).

After that, you will learn about Transfer Learning and how to apply transfer learning to your own deep Convolutional Neural Networks.

Object detection is also covered in this course. In the end, you will explore the applications of CNN such as Face recognition & Neural Style Transfer.

Who Should Enroll?

• Those who have intermediate Python Skills.

Interested to Enroll?

If yes, then start learning- Convolutional Neural Networks

3. Deep Learning– Udacity

Time to Complete- 4 months (If you spend 12 hours per week)

Rating- 4.7/5

This Nanodegree program will teach you how to build convolutional networks for image recognition, recurrent networks for sequence generation, and generative adversarial networks for image generation.

The instructor Sebastian Thrun will explain about detecting skin cancer with CNN. This is an advanced-level course to understand the concepts of CNN and deep learning. This is not for beginners.

Who Should Enroll?

• Those who have intermediate-level Python programming knowledge and experience with NumPy and pandas.
• And those who have math knowledge, including- algebra and some calculus.

Interested to Enroll?

If yes, then start learning– Deep Learning (Udacity)

4. Deep Learning in Python– Datacamp

Time to Complete- 20 hours

Type- Skill Track

This is a skill track offered by Datacamp. In this skill track, there are 5 courses.

This skill track will teach you about convolutional neural networks and how to use them to build much more powerful models which give more accurate results. 

Throughout this skill track, you will work on projects and learn how to accurately predict housing prices, credit card borrower defaults, and images of sign language gestures. This is not for beginners.

Who Should Enroll?

• Those who have previous knowledge in Machine Learning and Python Programming.

Interested to Enroll?

If yes, then start learning– Deep Learning in Python

5. Deep Learning: Convolutional Neural Networks in Python– Udemy

Rating- 4.7/5

Time to Complete- 12 hours

This course is all about Convolutional Neural networks (CNN).

In this course, you will learn the fundamentals of CNN and how to build a CNN using Tensorflow 2. After that, you will learn how to do image classification in Tensorflow 2 and how to use Embeddings in Tensorflow 2 for NLP.

If you are a beginner, then this course is not for you.

Who Should Enroll?

• Those who have an understanding of basic math (taking derivatives, matrix arithmetic, probability).

Interested to Enroll?

If yes, then check it out here– Deep Learning: Convolutional Neural Networks in Python

6. Intro to TensorFlow for Deep Learning– Udacity

Time to Complete- 2 months

This course will teach you about Convolutional Neural Networks and how to use a convolutional network to build more efficient models for Fashion MNIST.

This is a completely FREE course. During this course, you will work on a project where you will build a neural network that can recognize images of articles of clothing.

Who Should Enroll?

• Those who know Python programming and basic algebra.

Interested to Enroll?

If yes, then start learning- Intro to TensorFlow for Deep Learning

7. Become a Computer Vision Expert– Udacity

Rating- 4.7/5

Provider- Udacity

Time to Complete- 3 months (If you spend 10-15 hours/week)

This Nanodegree program will teach you basic image processing and building and customizing convolutional neural networks. 

Throughout the Nanodegree program, you will work on various projects such as facial keypoint detection, automatic image captioning, and landmark detection & tracking.

This Nanodegree Program is not for beginners. This is an advanced-level program where you will also learn techniques used in self-driving car navigation and drone flight.

Who Should Enroll?

• Those who have intermediate-level knowledge in Python, statistics, machine learning, and deep learning.
• And those who have worked before with a deep learning framework like TensorFlow, Keras, or PyTorch.

Interested to Enroll?

If yes, then check out all details here- Become a Computer Vision Expert

8. Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs– Udemy

Rating– 4.5/5

Provider- SuperDataScience Team

Time to Complete- 11 hours

In this course, you will learn what is Facial Recognition with OpenCV, object detection with SSD, and Image creation with GAN. 

This course also covers the concepts of artificial neural networks and convolutional neural networks.

Who Should Enroll?

• Those who have basic python programming knowledge and high-school-level math.

Interested to Enroll?

If yes, then check out all details here- Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs

And that’s all…So, these are the 8 Best Convolutional Neural Network Resources. Now, it’s time to wrap up.

Conclusion

I hope these 8 Best Convolutional Neural Network Resources will help you to learn CNN in detail. My aim is to provide you with the best resources for Learning. If you have any doubt or questions, feel free to ask me in the comment section.

Tell me in the comment section, which course you like.

All the Best!

Happy Learning!

Thank YOU!

Learn Deep Learning Basics here.

Though of the Day…

‘ Anyone who stops learning is old, whether at twenty or eighty. Anyone who keeps learning stays young.

– Henry Ford