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
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: Performance Tuning
- Category: Classification Algorithms
- Category: Applied Machine Learning
- Category: Model Evaluation
- Category: Logistic Regression
- Category: PyTorch (Machine Learning Library)
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Convolutional Neural Networks
- Category: Model Training
- Category: Transfer Learning
- Category: Fine-tuning
