The online two-day course Introduction to Deep Learning will be organized by AI Factory Austria AI:AT and Austrian Scientific Computing (ASC) from 3 to 4 March 2026. This course covers the essentials of neural networks, from artificial neural networks (ANNs) to convolutional neural networks (CNNs) for computer vision, recurrent neural networks (RNNs) for sequence processing and transfer learning. Participants will gain hands-on experience using PyTorch to build and train models on high-end GPUs on an HPC cluster.
Deep Learning (DL) has enjoyed a surge in popularity during the last decade. This is mainly owed to the fact that DL is computationally quite expensive and needs vast amounts of data to train useful models. Both computational resources and large datasets have become more readily available in recent years, leading to breakthroughs in DL applications. The course will cover the basic principles of fully connected neural networks, CNNs for computer vision, RNNs for text or speech recognition, transfer learning to leverage pretrained models, and touch on large language models (LLMs) which have become all the rage in the past few years.
This course is designed for software developers, data scientists, and researchers who want to transition from simply using AI tools to building, customizing, and deploying them. The course is open to participants from academia, industry, and public administration.
