Deep Learning Demystified: Hands-on Deep Learning for Non-CS Majors

What it is about

You will gain a practice-oriented understanding of Deep Learning with a focus on Computer Vision, neural networks, convolution operations and backpropagation. In the end you will be able to implement basic deep-learning projects, use frameworks such as TensorFlow/Keras/PyTorch, and assess societal and ethical implications.

What you will be able to do

• Understand and analyze architectures of neural networks
• Apply convolution operations and image processing
• Mathematically understand the mechanisms of backpropagation
• Preprocess, normalize and augment data
• Work with TensorFlow, Keras and PyTorch
• Implement practical deep-learning projects
• Reflect on ethical and societal implications of deep learning
• Strengthen teamwork and presentation skills in group projects

What the module consists of

• Übungaccompanies, reinforces and explains content of the lecture 'Introduction to Deep Learning'; focus on fundamentals and applications; practical projects and group work

Teaching method

• Praktische Projektefor hands-on experience (e.g. image classification, sentiment analysis)
• Interaktives Lernenuse of analogies, real-world examples and tools to explain complex concepts
• Gruppenzusammenarbeitpromotes teamwork through group projects and presentations
• Analyse von Fallstudiendeep dive into real-world applications and limits of deep learning