Deep Learning with PyTorch
Completed by Andrea Carolina Fontalvo Echavez
January 20, 2026
20 hours (approximately)
Andrea Carolina Fontalvo Echavez'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: Artificial Neural Networks
- Category: Applied Machine Learning
- Category: Model Evaluation
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: PyTorch (Machine Learning Library)
- Category: Classification Algorithms
- Category: Transfer Learning
- Category: Image Analysis
- Category: Deep Learning
- Category: Model Optimization
- Category: Logistic Regression
- Category: Convolutional Neural Networks
