This course covers everything from AI fundamentals to advanced Neural Networks with hands-on learning. You’ll explore machine learning types, key algorithms, deep learning, and model optimization. The course includes training neural networks, data preprocessing, and techniques for performance improvement. You'll work on real-world datasets with a personalized final project. By the end of this course, you will have a deep understanding of how machine learning models work, be able to build, train, and evaluate your own AI models, have a working machine learning pipeline using real-world data, and be prepared to explore more advanced AI topics.

Finite Element Analysis (FEA) has become an essential skill. This course covers theoretical and practical aspects of FEA applied to structural analysis. In the theoretical section, you will explore concepts like material resistance, beam models, finite element fundamentals, and how a FEA software works. The practical lessons will guide you through model preparation, meshing, local axis, boundary conditions, materials, loads, post-processing, key results to look for, and how to prepare a professional report. The course also features multiple examples based on a bulk carrier ship and a fast craft and culminates in a final project involving a planning motorboat, which will allow you to apply everything you have learned in a practical context.