Deep Learning with PyTorch
Completed by Jim Espinola
June 8, 2026
20 hours (approximately)
Jim Espinola'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 Intelligence and Machine Learning (AI/ML)
- Category: Model Optimization
- Category: Model Training
- Category: Image Analysis
- Category: Classification Algorithms
- Category: PyTorch (Machine Learning Library)
- Category: Artificial Neural Networks
- Category: Model Evaluation
- Category: Convolutional Neural Networks
- Category: Transfer Learning
- Category: Applied Machine Learning
- Category: Deep Learning
