Deep Learning with PyTorch
Completed by Christoph Maass
February 28, 2026
20 hours (approximately)
Christoph Maass'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: Supervised Learning
- Category: Artificial Neural Networks
- Category: Transfer Learning
- Category: Model Evaluation
- Category: Logistic Regression
- Category: PyTorch (Machine Learning Library)
- Category: Statistical Methods
- Category: Model Optimization
- Category: Applied Machine Learning
- Category: Classification Algorithms
- Category: Image Analysis
