Deep Learning Fundamentals

The further one dives into the ocean, the more unfamiliar the territory can become. Deep learning, at the surface might appear to share similarities. This course is designed to get you hooked on the nets and coders all while keeping the school together.

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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.

Please note that version 2.0 of this course was released on August 23, 2017. Please refer to the Change Log section in the course for a detailed description of the changes and updates.

Course Syllabus

  • Module 1 - Introduction to Deep Learning
    1. Why Deep Learning?
    2. What is a neural network?
    3. Three reasons to go Deep
    4. Your choice of Deep Net
    5. An old problem: The Vanishing Gradient
  • Module 2 - Deep Learning Models
    1. Restricted Boltzmann Machines
    2. Deep Belief Nets
    3. Convolutional Networks
    4. Recurrent Nets
  • Module 3 - Additional Deep Learning Models
    1. Autoencoders
    2. Recursive Neural Tensor Nets
    3. Deep Learning Use Cases
  • Module 4 - Deep Learning Platforms and Software Libraries
    1. What is a Deep Learning Platform?
    3. Dato GraphLab
    4. What is a Deep Learning Library?
    5. Theano
    6. Caffe
    7. TensorFlow

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.

Recommended skills prior to taking this course

  • None


  • None

Note: This course is an introductory course and does not have any hands-on lab. After completing this course, it is recommended to take "Deep learning with TensorFlow" course

Note: Though this course does not have any hands-on lab, still you can try PowerAI to understand different deep learning libraries better. PowerAI speeds up deep learning and AI. Built on IBM's Power Systems, PowerAI is a scalable software platform that accelerates deep learning and AI with blazing performance for individual users or enterprises. The PowerAI platform supports popular machine learning libraries and dependencies including Tensorflow, Caffe, Torch, and Theano. You can download a free version of PowerAI here.

Course Creator Info

Introduction to Deep Learning


DeepLearning.TV is all about Deep Learning, the field of study that teaches machines to perceive the world. Starting with a series that simplifies Deep Learning, DeepLearning.TV features topics such as How To’s, reviews of software libraries and applications, and interviews with key individuals in the field. Through a series of concept videos showcasing the intuition behind every Deep Learning method, we will show you that Deep Learning is actually simpler than you think. Our goal is to improve your understanding of the topic so that you can better utilize Deep Learning in your own projects. We hope to provide a window into the cutting edge of Deep Learning and bring you up to speed on what’s currently happening in the field.