Convolutional Neural Networks

Instructor: Andrew Ng , Kian Katanforoosh , Younes Bensouda Mourri

Intermediate Level • 2 weeks at 10 hours a week • Flexible Schedule

Skills You'll Gain

Image Analysis
Artificial Neural Networks
Deep Learning
Data Processing
Computer Vision
Applied Machine Learning
Algorithms
PyTorch (Machine Learning Library)
Tensorflow
Artificial Intelligence

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

Implement the foundational layers of CNNs (pooling, convolutions) and stack them properly in a deep network to solve multi-class image classification problems.

Discover some powerful practical tricks and methods used in deep CNNs, straight from the research papers, then apply transfer learning to your own deep CNN.

Apply your new knowledge of CNNs to one of the hottest (and most challenging!) fields in computer vision: object detection.

Explore how CNNs can be applied to multiple fields, including art generation and face recognition, then implement your own algorithm to generate art and recognize faces!