PyTorch Online Course

PyTorch Online Course

PyTorch, developed by Facebook, is one of the leading deep learning frameworks, known for its flexibility, ease of use, and strong community support. This course is designed to take you from foundational deep learning concepts to building and deploying your own models using PyTorch.

You’ll begin by understanding the fundamentals of deep learning, followed by hands-on experience with tensors—learning how to create, manipulate, and leverage PyTorch’s Autograd for automatic differentiation and gradient computation.

From there, you’ll build linear regression models from the ground up and move on to advanced classification techniques, covering both multilabel and multiclass classification.

By the end of this course, you'll have a solid grasp of PyTorch's core components and the confidence to design, train, and deploy robust deep learning models.

Who should take this Course?

This course is ideal for Python developers, data science beginners, AI enthusiasts, and machine learning practitioners who want to strengthen their deep learning capabilities using PyTorch. Whether you're starting out or looking to level up your skills, this course offers a structured and practical learning experience.

Prerequisites:

A basic understanding of Python is required to follow along with the content effectively.

Course Curriculum

• Course Overview and System Setup

• Machine Learning
• Deep Learning Introduction
• Model Evaluation
• Neural Network from Scratch
• Tensors
• PyTorch Modeling Introduction
• Classification Models
• CNN: Image Classification
• CNN: Audio Classification
• CNN: Object Detection
• Style Transfer
• Pre-Trained Networks and Transfer Learning
• Recurrent Neural Networks
• Recommender Systems
• Autoencoders
• Generative Adversarial Networks
• Graph Neural Networks
• Transformers
• PyTorch Lightning
• Semi-Supervised Learning
• Natural Language Processing (NLP)
• Miscellaneous Topics
• Model Debugging
• Model Deployment
• Final Section