Advanced PyTorch Techniques and Applications
Completed by Ramitha Chowdary S
March 17, 2026
11 hours (approximately)
Ramitha Chowdary S'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: Machine Learning Methods
- Category: Deep Learning
- Category: Generative Adversarial Networks (GANs)
- Category: Model Deployment
- Category: Artificial Neural Networks
- Category: PyTorch (Machine Learning Library)
- Category: Natural Language Processing
- Category: Model Evaluation
- Category: Network Model
- Category: Embeddings
- Category: Unsupervised Learning
