Deep Learning with PyTorch
Completed by Reilly Osadchey
February 18, 2026
20 hours (approximately)
Reilly Osadchey'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: Image Analysis
- Category: Classification Algorithms
- Category: Transfer Learning
- Category: Model Evaluation
- Category: Logistic Regression
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Applied Machine Learning
- Category: Artificial Neural Networks
- Category: Model Optimization
- Category: Deep Learning
- Category: PyTorch (Machine Learning Library)
- Category: Convolutional Neural Networks
