This free course presents a holistic approach to Deep Learning and answers fundamental questions about what Deep Learning is and why it matters.

About This Course

Get a crash course on the what there is to learn and how to go about learning more. Deep Learning presents a simplified explanation of some of the hottest topics in data science today:

• What is Deep Learning?
• What are are convolutional neural networks?
• Why is deep learning so powerful and what can it be used for?
• Be part of a rapidly growing field in data science; there’s no better time than now to get started with neural networks.

Course Syllabus

• Module 1 – Deep Learning Concepts
  1. What is a neural network?
  2. Why Deep Learning?
  3. How to choose between deep neural networks?
  4. An old problem: The Vanishing Gradient
  5. Restricted Boltzmann Machines
  6. Deep Belief Networks

• Module 2 – Deep Learning Concepts Continued
  1. Convolutional Networks
  2. Recurrent Nets
  3. Autoencoders
  4. Recursive Neural Tensor Nets
  5. Deep Learning Use Cases

• Module 3 – Platforms for Deep Learning
  1. What is a Deep Learning Platform?
  2. H2O.ai
  3. Dato GraphLab

• Module 4 – Deep Learning Software Libraries
  • What is a Deep Learning Library?
  • Theano
  • Deeplearning4j
  • Torch
  • Caffe

General Information

• This course is free.
• It is self-paced.
• It can be taken at any time.
• It can be audited as many times as you wish.

How to Enroll: 

Enroll Now

1. Choose your desired certificate program on the IBM website.
2. Create an Amazon if you don’t have one.
3. Select specific courses within your chosen program.
4. Enroll in courses, and pay if necessary.
5. Access course materials and complete requirements.
6. Prepare for and take certification exams if required.
7. Earn your certificate upon successful completion.
8. Be aware of maintenance or renewal requirements, if applicable.

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