Deep Learning with PyTorch
Completed by Mujahed Damery
February 27, 2026
20 hours (approximately)
Mujahed Damery'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: Model Training
- Category: Model Optimization
- Category: Transfer Learning
- Category: Artificial Neural Networks
- Category: Classification Algorithms
- Category: Statistical Methods
- Category: Supervised Learning
- Category: Convolutional Neural Networks
- Category: PyTorch (Machine Learning Library)
- Category: Deep Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
