Deep Learning with PyTorch
Completed by Moosa Yasin
October 9, 2025
20 hours (approximately)
Moosa Yasin'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: Classification Algorithms
- Category: Convolutional Neural Networks
- Category: Deep Learning
- Category: Transfer Learning
- Category: Model Training
- Category: Model Evaluation
- Category: Image Analysis
- Category: PyTorch (Machine Learning Library)
- Category: Model Optimization
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Applied Machine Learning
