Deep Learning with PyTorch
Completed by Samad Rezaei
January 10, 2026
18 hours (approximately)
Samad Rezaei's account is verified. Coursera certifies their successful completion of Deep Learning with PyTorch
What you will learn
Key concepts on Softmax regression and understand its application in multi-class classification problems.
How to develop and train shallow neural networks with various architectures.
Key concepts of deep neural networks, including techniques like dropout, weight initialization, and batch normalization.
How to develop convolutional neural networks, apply layers and activation functions.
Skills you will gain
- Category: PyTorch (Machine Learning Library)
- Category: Artificial Neural Networks
- Category: Model Evaluation
- Category: Classification Algorithms
- Category: Image Analysis
- Category: Model Optimization
- Category: Deep Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Applied Machine Learning
- Category: Model Training
- Category: Convolutional Neural Networks
