Advanced PyTorch Techniques and Applications
Completed by M AHAMED SAHUL HAMEED
March 14, 2026
11 hours (approximately)
M AHAMED SAHUL HAMEED'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: Supervised Learning
- Category: Generative Model Architectures
- Category: Model Optimization
- Category: Flask (Web Framework)
- Category: Artificial Neural Networks
- Category: Vision Transformer (ViT)
- Category: Dimensionality Reduction
- Category: Model Training
- Category: Embeddings
- Category: Unsupervised Learning
- Category: PyTorch (Machine Learning Library)
- Category: Generative Adversarial Networks (GANs)
