Fundamentals of Deep Learning Training in Sweden

An understanding of fundamental programming concepts in Python such as functions, loops, dictionaries, and arrays.

• Learn the fundamental techniques and tools required to train a deep learning model
• Gain experience with common deep learning data types and model architectures
• Enhance datasets through data augmentation to improve model accuracy
• Leverage transfer learning between models to achieve efficient results with less data and computation
• Build confidence to take on your own project with a modern deep learning framework

• Meet the instructor.
• Create an account at courses.nvidia.com/join

• Train your first computer vision model to learn the process of training.
• Introduce convolutional neural networks to improve accuracy of predictions in vision applications.
• Apply data augmentation to enhance a dataset and improve model generalization

• Integrate a pre-trained image classification model to create an automatic doggy door.
• Leverage transfer learning to create a personalized doggy door that only lets in your dog.
• Train a model to autocomplete text based on New York Times headlines.

• Apply computer vision and natural language processing to automatically caption images.
• Create and train an advanced model with multiple input layers and data types.
• Build training sequences that join image and language data.
• Improve training speed by combining transfer learning and feature extraction.

• Review key learnings and answer questions.
• Complete the assessment and earn a certificate.
• Complete the workshop survey.
• Learn how to set up your own AI application development environment.