Course 7: Pytorch


  • Basic knowledge of linear algebra and calculus
  • Programming experience – Python Language and data processing libraries (Numpy and Matplotlib)
  • Neural network experience

Who is this course for?

  • Students who complete the python and Basic AI and ML courses and want to advance more.
  • Students who have not studied Pytorch for learning Artificial Intelligence and Machine Learning.
  • People who want to get a Pytorch certificate for their career.

What you'll get after completing this course:

  • Loading and normalizing datasets
  • Building the model layers
  • Automatic differentiation
  • Learn about the optimization loop
  • Load and run model predictions
  • The full model building process
  • Introduction to processing image data
  • Training a simple dense neural network
  • Use a convolutional neural network
  • Train multi-layer convolutional neural network
  • Use a pre-trained netwrok with transfer learning
  • Solving vision problems with MobileNet
  • Representing text as Tensors
  • Bag of Words and TF-IDF
  • Represent words with embeddings
  • Capture patterns with recurrent neural networks
  • Generate text with recurrent networks
  • Understand audio data and concepts
  • Audio transformations and visualizations
  • Build the speech model

Do you have more questions?

Contact us

201 S. Grand Ave., 1st Floor New York City, NY 28020

Tell us a little about yourself and we’ll help with the rest. Our convenient online application tool only takes 10 minutes to complete.

After you submit your application, an admissions representative will contact you and will help you to complete the process.

Once you’ve completed your application and connected with an admissions representative, you’re ready to create your schedule.


Are you ready to begin this journey for yourself?