Advanced PyTorch Techniques and Applications
Completed by Clement CHARRUEL
January 30, 2026
11 hours (approximately)
Clement CHARRUEL's account is verified. Coursera certifies their successful completion of Advanced PyTorch Techniques and Applications
What you will learn
Create and assess ML models for specific datasets, evaluating performance with proper metrics.
Design autoencoders for dimensionality reduction and build GANs for data simulation, analyzing quality.
Develop Graph Neural Networks for graph data and implement Transformers, including Vision Transformers.
Enhance models with semi-supervised learning using limited data, and deploy them with Flask on Google Cloud.
Skills you will gain
- Category: Flask (Web Framework)
- Category: Supervised Learning
- Category: Deep Learning
- Category: Model Optimization
- Category: Embeddings
- Category: PyTorch (Machine Learning Library)
- Category: Unsupervised Learning
- Category: Generative Adversarial Networks (GANs)
- Category: Network Model
- Category: Model Deployment
- Category: Vision Transformer (ViT)
- Category: Dimensionality Reduction
