• Length:
    16 Weeks
  • Effort:
    6–9 hours per week
  • Price:

    FREE
    Add a Verified Certificate for $2,250 USD

  • Institution
  • Subject:
  • Level:
    Advanced
  • Language:
    English
  • Video Transcript:
    English
  • Course Type:
    Instructor-led on a course schedule

Prerequisites

Knowledge of probabilistic methods in electrical and computer engineering (ECE 302 at Purdue) and undergraduate linear algebra.

About this course

Skip About this course

This 3-credit-hour, 16-week course covers the fundamentals of deep learning. Students will gain a principled understanding of the motivation, justification, and design considerations of the deep neural network approach to machine learning and will complete hands-on projects using TensorFlow and Keras.

What you'll learn

Skip What you'll learn
  • Justify the development state-of-the-art deep learning algorithms.
  • Make design choices regarding the construction of deep learning algorithms.
  • Implement, optimize and tune state-of-the-art deep neural network architectures.
  • Identify and address the security aspects of state-of-the-art deep learning algorithms.
  • Examine open research problems in deep learning and propose approaches in the literature to tackle them.

Module 1: Introduction to Deep Feedforward Networks

    • Gradient-based learning
    • Sigmoidal output units
    • Back propagation

Module 2: Regularization for Deep Learning

    • Regularization strategies
    • Noise injection
    • Ensemble methods
    • Dropout

Module 3: Optimization for Training Deep Models

    • Optimization algorithms: Gradient, Hessian-Free, Newton
    • Momentum
    • Batch normalization

Module 4: Convolutional Neural Networks

    • Convolutional kernels
    • Downsampled convolution
    • Zero padding
    • Backpropagating convolution

Module 5: Recurrent Neural Networks

    • Recurrence relationship & recurrent networks
    • Long short-term memory (LSTM)
    • Back propagation through time (BPTT)
    • Gated and simple recurrent units
    • Neural Turing machine (NTM)

Meet your instructors

Aly El Gamal
Assistant Professor, Electrical and Computer Engineering
Purdue University

Pursue a Verified Certificate to highlight the knowledge and skills you gain
$2,250 USD

View a PDF of a sample edX certificate
  • Official and Verified

    Receive an instructor-signed certificate with the institution's logo to verify your achievement and increase your job prospects

  • Easily Shareable

    Add the certificate to your CV or resume, or post it directly on LinkedIn

  • Proven Motivator

    Give yourself an additional incentive to complete the course

  • Support our Mission

    edX, a non-profit, relies on verified certificates to help fund free education for everyone globally

Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.