Introduction Room: Hörsaal 1. Meet the instructor. 2. Create an account at [courses.nvidia.com/join][1] [1]: http://courses.nvidia.com/join

The Mechanics of Deep Learning Room: Hörsaal Explore the fundamental mechanics and tools involved in successfully training deep neural networks: 1. Train your first computer vision model to learn the process of training. 2. Introduce convolutional neural networks to improve accuracy of predictions in vision applications. 3. Apply data augmentation to enhance a dataset and improve model generalization.

Pre-trained Models and Large Language Models Room: Hörsaal Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data: 1. Integrate a pre-trained image classification model to create an * automatic doggy door. 2. Leverage transfer learning to create a personalized doggy door that only lets in your dog. 3. Use a Large Language Model (LLM) to answer questions based on provided text.

Final Project: Object Classification Room: Hörsaal Apply computer vision to create a model that distinguishes between fresh and rotten fruit: 1. Create and train a model that interprets color images. 2. Build a data generator to make the most out of small datasets. 3. Improve training speed by combining transfer learning and feature extraction. 4. Discuss advanced neural network architectures and recent areas of research where students can further improve their skills.

Final Review Room: Hörsaal 1. Review key learnings and answer questions. 2. Complete the assessment and earn a certificate. 3. Complete the workshop survey. 4. Learn how to set up your own AI application development environment.