The HCAIM (Human-Centered AI Master) program includes learning materials on AI modelling as part of Modelling (Module A), focusing on the initial phase of the MLOps lifecycle. This phase emphasizes foundational activities such as data extraction, analysis, preparation, model training, and manual validation.

The Practical Focus lesson plan on AI modelling combines theoretical lectures and practical exercises. Key areas covered include the data analysis process, data preparation, and exploration, followed by supervised machine learning techniques such as linear regression, decision trees, support vector machines (SVMs), and neural networks. The module also delves into unsupervised learning methods and their applications.

Additionally, the program explores machine learning applications, particularly in natural language processing (NLP). Each topic includes a lecture to introduce the concepts and practical sessions to apply these techniques on real-world data. 

This module is designed to provide students with the necessary skills to implement AI models effectively and ethically across various domains. For more information, students can visit the HCAIM consortium’s homepage.