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The course begins with an overview of PyTorch, including model classes, datasets, data loaders and the training loop. Next the role and power of transfer learning is addressed along with how to use it with pretrained models. Practical lab exercises cover multiple topics including: image classification, object detection, sentiment analysis, text classification, and text generation/completion. Learners also will use their data to fine-tune existing models and leverage third-party APIs.