The rapid advances in artificial intelligence are opening up new possibilities for the analysis of data in materials science. In particular, deep learning and convolutional neural networks (CNNs) are revolutionizing automated data processing. The training course “Deep Learning – Fundamentals and Applications in Materials Science” provides a practical introduction to how these technologies can be used to classify and segment image and table data. 

It is crucial for companies working in materials science to exploit the potential of these modern analysis methods. AI-supported processes not only make it possible to process large amounts of data faster, but also to achieve more precise results. In the training, participants learn how to use deep learning effectively to make data-based decisions and optimize their research and development processes.  

Why you should attend:  
Participating in this training offers numerous advantages for your company: 

• Fundamentals of the software tools: You will learn how to use PyTorch, FastAi and Jupyter Notebook to effectively integrate these powerful tools into your projects. 
• Principles of Deep Learning: You will learn the basic concepts and how Deep Learning is used as a machine learning method to analyze complex data. 
• Specific applications in materials science: The training provides practical insights into the application of Deep Learning to materials science problems and shows how these can be implemented in industrial practice.  
• Theory of Neural Networks: Gain a deeper understanding of the structure and functioning of neural networks to make informed decisions when implementing AI solutions. 
• Classification Models and Image Analysis: Learn how to efficiently classify image data using CNNs and how to tackle specific use cases, such as classifying 2-phase steels.  
• Exchange with experts: Discuss your specific challenges with experienced professionals and benefit from their expertise to develop solutions for your own use cases.  

Target audience of the training
This training is aimed at scientists and engineers who already have basic programming skills in Python, Matlab or other programming languages. It is recommended that you have a basic understanding of areas such as arithmetic operations, control structures, linear algebra and nonlinearity.  

Enroll today to expand your AI knowledge, analyze your materials science data more efficiently, and advance your organization technologically. The combination of theory and practice will help you gain a real competitive advantage in your industry.