Introduction to Deep Learning

Training overview
Professional Course
Virtual Classroom
16 weeks
From 2,250 USD

Start dates
2,250 USD
Inquire for more information

Course description

Introduction to Deep Learning

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.

Want to find out more?

Who should attend?


This course is designed for students who have an undergraduate degree in electrical and computer engineering, computer science, or similar. Undergrauadate coursework in probabilistic methods in electrical and computer engineering and linear algebra is recommended before taking this course.

Training content

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)

Course delivery details

This course is offered through Purdue University, a partner institute of EdX.

6-9 hours per week


  • Verified Track -$2250
  • Audit Track - Free

Certification / Credits

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.

About edX


edX For Business helps leading companies upskill their labor forces by making the world’s greatest educational resources available to learners across a wide variety of in-demand fields. edX For Business delivers high-quality corporate eLearning to train and engage your employees...

Read more and show all training delivered by this supplier

Contact this provider

Fill out your details to find out more about Introduction to Deep Learning.

  Contact the provider

  Get more information

  Register your interest

Country *

Contact info


141 Portland Street
02139 Cambridge Massachusetts

 Show phone number

Request Information

Have a question about this course? Fill out this form and the provider will get in touch with you shortly

View again
Supplier Directory
Join our Supplier Directory to:
- Gain Traffic
- Get Noticed
- Showcase Your Services
- Free Listing Available