Convolutional Neural Networks (CNN) Courses and Certifications

Convolutional Neural Networks

8 ratings

Build convolutional neural networks and residual variants, apply transfer learning, and implement object detection, face recognition, and neural style transfer for art generation.

• Coursera
• 4 weeks, 9 hours a week
• Self-Paced
• Paid Course

Convolutional Neural Networks in Python: CNN Computer Vision

1471 ratings at Udemy

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

• Udemy
• 7 hours 47 minutes
• Self-Paced
• Paid Course

Image Modeling with Keras

92 ratings at DataCamp

Learn to Use Convolutional Neural Networks in Python Image model often requires deep learning methods that use data to train neural network algorithms to do various machine learning tasks.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Building Convolutional Neural Networks for Computer Vision

Learn to build and train convolutional neural networks in PyTorch for image classification, transfer learning, anomaly detection, object detection, and semantic segmentation.

• Udacity
• 13 hours
• Self-Paced
• Paid Course

Convolutional Neural Networks

Build and adapt convolutional neural networks in PyTorch for image classification, anomaly detection, denoising, object detection, and semantic segmentation.

• Udacity
• 21 hours
• Self-Paced
• Paid Course

Introduction to Deep Learning

25 ratings

Deep Learning is subset of machine learning focused on extracting patterns from data using neural networks and use those patterns to inform the learning tasks.

• YouTube
• 2 days 7 hours 16 minutes
• Self-Paced
• Free Video

Introduction to Drawing Recognition and CNN Fundamentals

Learn CNN fundamentals by exploring MNIST digit data and building, training, evaluating, and using models to recognize hand-drawn sketches.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Drawing Recognition with CNNs for Sketches

Build and evaluate a convolutional neural network that recognizes hand-drawn sketches, using confusion matrices and misclassification visualizations to improve performance.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Convolutional Neural Networks in TensorFlow

8225 ratings at Coursera

Improve ConvNet image classifiers in TensorFlow: train on the Cats vs Dogs dataset, curb overfitting with augmentation and dropout, apply transfer learning, and handle multiclass classification.

• Coursera
• 4 weeks, 4 hours a week
• Self-Paced
• Paid Course

Amazon;  Amazon Web Services;  Facebook Career Certificate

Deep Learning

15 ratings

Build and train neural networks in PyTorch across CNNs, RNNs, transformers, and GANs for image, language, and generative tasks.

• Udacity
• 61 hours
• Self-Paced
• Paid Course

Deep Learning: Convolutional Neural Networks in Python

7394 ratings at Udemy

Tensorflow 2 CNNs for Computer Vision, Natural Language Processing (NLP) +More! For Data Science & Machine Learning

• Udemy
• 13 hours 54 minutes
• Self-Paced
• Paid Course

Coursera

Visualizing Filters of a CNN using TensorFlow

85 ratings at Coursera

See what a CNN sees: use gradient ascent in TensorFlow to generate images that maximally activate filters from different layers of the VGG16 model.

• Coursera
• 1 hour 20 minutes
• Self-Paced
• Paid Course

Fundamentals of CNNs and RNNs

40 ratings at Coursera

An introductory survey of CNN and RNN architectures, from convolution and pooling to recurrent models including LSTMs and GRUs.

• Coursera
• 5 weeks, 1 hour a week
• Self-Paced
• Paid Course

EDUCBA

Master CNNs with Python: Build, Train & Evaluate Models

19 ratings at Coursera

Build, train, and evaluate CNN image classification models in Python, from project setup and architecture to image preprocessing, augmentation, predictions, and accuracy comparison.

• Coursera
• 2 weeks, 3 hours a week
• Self-Paced
• Paid Course

Coursera

CNNs with TensorFlow: Basics of Machine Learning

Build convolutional neural networks in TensorFlow to classify clothing images into 10 categories, adapting network components and evaluating models to improve accuracy.

• Coursera
• 2 hours 15 minutes
• Self-Paced
• Paid Course