Deep Learning with PyTorch
Completed by Djibril Gueye
January 13, 2026
20 hours (approximately)
Djibril Gueye'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: Classification Algorithms
- Category: Transfer Learning
- Category: PyTorch (Machine Learning Library)
- Category: Artificial Neural Networks
- Category: Logistic Regression
- Category: Model Evaluation
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Applied Machine Learning
- Category: Convolutional Neural Networks
- Category: Model Training
- Category: Deep Learning
