Deep Learning


Course Details

About this Course

Deep learning is a subfield of artificial intelligence that is inspired by how the human brain works, a concept often referred to as neural networks. In the last decade we’ve seen significant development of deep learning methods that enable state-of-the-art performance for many tasks, including image classification, audio classification and natural language processing. In this course, you’ll gain hands-on experience in both feedforward and recurrent neural networks.


  • Techniques for constructing multilayer perceptron models, embedding models, and recurrent and convolutional neural network models
  • Ways to use regularization, dropout, and batch normalization to improve generalization
  • How to apply gradient descent and adaptive gradient descent


  • Gain experience in both R and Python programming
  • Apply techniques using popular open-source tools, including scikit-learn, Anaconda3, Apache Spark, Tensorflow and Keras.

Program Overview

Complete the courses listed below to earn the certificate. You may be able to take individual courses without enrolling in the certificate program; check the course pages for details.