Learning

Computational Materials Design with DFT and Data-Driven Methods

Quantum Mechanics Fundamentals → Capstone Project in Materials Design

This path equips learners with the skills to use computational methods for materials design, focusing on density functional theory (DFT) for property prediction and data-driven approaches for high-throughput screening and inverse design. It progresses from fundamental quantum chemistry and solid-state physics to practical database mining and machine learning applications, culminating in a capstone project.