欧美福利100000

Purpose

This programme aims to equip students with practical and theoretical competence in data science and machine learning for nuclear engineering applications. Students will learn Python fundamentals, data wrangling, exploratory data analysis, and data validation techniques. They will gain hands-on experience with supervised methods, including regression, classification, ensemble learning, and neural networks, as well as unsupervised techniques such as clustering and dimensionality reduction. Model evaluation strategies, including cross-validation, grid search, and metrics assessment, will be emphasized. Finally, students will apply these methods to a nuclear engineering problem, integrating data science and machine learning skills to analyze, interpret, and solve practical engineering challenges.

Admission Requirements

Applicants require at least a Bachelor of Engineering (BEng) or Bachelor of Science (BSc). A Science, Engineering, or technical degree at NQF Level 7, including one year of Physics and two years of Mathematics.

Selection Process

Selection is based on academic merit.

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