Deep Learning with PyTorch
Completed by Maurice Abou Jaoude
August 27, 2026
20 hours (approximately)
Maurice Abou Jaoude'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: Machine Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Model Optimization
- Category: Artificial Neural Networks
- Category: Deep Learning
- Category: Statistical Methods
- Category: PyTorch (Machine Learning Library)
- Category: Classification Algorithms
- Category: Applied Machine Learning
- Category: Supervised Learning
