Professional Course

PyTorch Basics for Machine Learning

edX, Online
5 weeks
39 USD
Next course start
Start anytime See details
Self-paced Online
5 weeks
39 USD
Next course start
Start anytime See details
Self-paced Online
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Course description

PyTorch Basics for Machine Learning

This course is the first part in a two part course and will teach you the fundamentals of Pytorch while providing the necessary prerequisites you need before you build deep learning models.

We will start off with PyTorch's tensors in one dimension and two dimensions , you will learn the tensor types an operations, PyTorchs Automatic Differentiation package and integration with Pandas and Numpy. This is followed by an in-depth overview of the dataset object and transformations; this is the first step in building Pipelines in PyTorch.

In module two we will learn how to train a linear regression model. You will review the fundamentals of training your model including concepts such as loss, cost and gradient descent. You will learn the fundamentals of PyTorch including how to make a prediction using PyTorch's linear class and custom modules. Then determine loss and cost with PyTorch. Finally you will implement gradient descent via first principles.

In module three you will train a linear regression model via PyTorch's build in functionality, developing an understanding of the key components of PyTorch. This will include how to effectively train PyTorch's custom modules using the optimizer object, allowing you an effective way to train any model. We will introduce the data loader allowing you more flexibility when working with massive datasets . You will learn to save your model and training in applications such as cross validation for hyperparameter selection, early stopping and checkpoints.

Upcoming start dates

1 start date available

Start anytime

  • Self-paced Online
  • Online
  • English

Who should attend?



Training content

  • Tensors 1D
  • Two-Dimensional Tensors
  • Derivatives In PyTorch
  • Dataset
  • Prediction Linear Regression
  • Training Linear Regression
  • Loss
  • Gradient Descent
  • Cost
  • Training PyTorch
  • Gradient Descent
  • Mini-Batch Gradient Descent
  • Optimization in PyTorch
  • Training and Validation
  • Early stopping
  • Multiple Linear Regression Prediction
  • Multiple Linear Regression Training
  • Linear regression multiple outputs
  • Multiple Output Linear Regression Training
  • Final project

Course delivery details

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

4-5 hours per week


  • Verified Track -$39
  • Audit Track - Free

Certification / Credits

What you'll learn

  • Build a Machine learning pipeline in PyTorch
  • Train Models in PyTorch.
  • Load large datasets
  • Train machine learning applications with PyTorch
  • Have the prerequisite Knowledge to apply to deep learning
  • how to incorporate and Python libraries such as Numpy and Pandas with PyTorch

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