Machine Learning Applications: Predicting Carbon Nanotube Properties

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Introduces fundamental machine learning concepts, covering regression, classification, dimensionality reduction, and deep generative models.

Introduction to Machine Learning: Course Overview and Basics

Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

Thermo-mechanics: Thermal and Mechanical Problems

Explores thermal and mechanical problems in thermo-mechanics, covering the heat equation, total strain, and stress analysis modeling.

Structural Mechanics Fundamentals

Covers the fundamental concepts of structural mechanics, including materials properties, stress and strain, equilibrium of forces and moments, and elementary structures.

Axial Loading: Stress and Strain in Deformable Bodies

Covers axial loading, stress, strain, and their implications in deformable bodies.

Towards Sustainable Composites

Explores sustainable composite solutions, including recycling, end-of-life strategies, and hydrogen storage.

Machine Learning Fundamentals

Covers the fundamental principles and methods of machine learning, including supervised and unsupervised learning techniques.

Properties of Materials and Structural Design

Covers elasticity, common construction materials, structural design principles, and an elevator design example.

Cost Modelling for Sustainable Innovation

Introduces cost modelling as a tool for sustainable innovation and covers topics such as transport CO2 emissions and material properties.

Machine Learning: Fundamentals and Applications

Introduces machine learning basics, covering data segmentation, clustering, classification, and practical applications like image classification and face similarity.