Deep Learning with PyTorch
Completed by Taha Enes Aslantürk
July 10, 2025
20 hours (approximately)
Taha Enes Aslantürk'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: Model Training
- Category: PyTorch (Machine Learning Library)
- Category: Artificial Neural Networks
- Category: Applied Machine Learning
- Category: Classification Algorithms
- Category: Image Analysis
- Category: Convolutional Neural Networks
- Category: Model Evaluation
- Category: Transfer Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Logistic Regression
- Category: Model Optimization
