Deep Learning with PyTorch
Completed by Filipe Braiman de Carvalho
January 25, 2026
20 hours (approximately)
Filipe Braiman de Carvalho's account is verified. Coursera certifies their successful completion of Deep Learning with PyTorch
What you will learn
Get hands-on experience using PyTorch to build and deploy AI systems and complete a portfolio-worthy project.
Develop and train shallow neural networks with various architectures and apply Softmax regression in multi-class classification problems.
Explore deep neural networks, including techniques such as dropout, weight initialization, and batch normalization.
Gain practical experience with convolutional neural networks, exploring layers, activation functions, and more.
Skills you will gain
- Category: Logistic Regression
- Category: Transfer Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Artificial Neural Networks
- Category: Machine Learning
- Category: Statistical Methods
- Category: PyTorch (Machine Learning Library)
- Category: Model Optimization
- Category: Deep Learning
- Category: Computer Vision
- Category: Model Training
- Category: Convolutional Neural Networks
