EDIBM · on edX
PyTorch Basics for Machine Learning
Beginner 15 hours English Verified CertificateFREE
About this course
PyTorch Basics for Machine Learning is the first half of IBM's PyTorch sequence, covering the fundamentals: tensors, automatic differentiation, and building your first simple models. It's the on-ramp before the deep learning course that follows it.
The honest take: this is intentionally foundational — if you already know PyTorch basics from elsewhere, skip ahead to the deep learning course. For genuine PyTorch beginners, it's a clean, focused starting point rather than an overwhelming firehose.
What you'll learn
Work with PyTorch tensors and operations
Understand automatic differentiation (autograd)
Build basic linear and logistic regression models
Use PyTorch's data loading utilities
Train a first simple model end-to-end
Prepare for deep learning model building
This course includes
15h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
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Instructor
I
IBM
edX instructor
— learners— courses — instructor rating
Taught by IBM's data science and AI training team.
Requirements
- Basic Python knowledge
Who this course is for
- PyTorch beginners
- Python developers new to deep learning frameworks
About this provider
ED
edX
Non-profit online learning platform founded by Harvard and MIT. 45M+ learners worldwide.
4.5 trust score
Frequently asked questions
No — this is the entry point, assuming only basic Python.
Audit free; verified certificate is $199.
About 15 hours.
Deep Learning with Python and PyTorch, which builds on these fundamentals.
No — it's specifically about PyTorch's tensor/autograd system, not general Python programming.