The subject “Structure and Characterization Techniques for Advanced Materials”, offered as part of the Master's Program in Engineering, Processing, and Characterization of Materials at Universitat Politècnica de València (UPV), provides an ideal platform for integrating Big Data into education. With a focus on advanced techniques for thermal, mechanical, and microscopic characterization, this initiative seeks to transform the learning experience through the analysis and correlation of large volumes of experimental data. Its primary objective is to prepare students to address real-world challenges in both industrial and academic sectors by equipping them with tools to more effectively relate material properties to their internal structure.

The strategy includes an introductory module designed to familiarize students with data management and analysis tools such as Python or MATLAB. These skills are then applied in the core areas of the course. In the domain of advanced materials' structure and applications, students will analyze patterns and trends in experimental data, gaining deeper insights into the behavior of biomimetic and smart materials. In the characterization techniques module, Big Data will be applied to datasets obtained through advanced tools such as electron microscopy or differential scanning calorimetry to correlate results and develop predictive models.

Furthermore, group projects based on real-world problems will foster essential skills such as teamwork, data-driven decision-making, and effective communication of findings. These projects align with the transversal competencies outlined in the course syllabus. Evaluation will include specific rubrics assessing the quality of data analysis, interpretation of results, and presentation of clear and professional visualizations. Projects will hold significant weight in the final grade, encouraging active participation and deep learning.

The integration of Big Data into this course not only strengthens students’ technical and analytical skills but also bridges education with current labor market demands and technological trends, ensuring a comprehensive and forward-looking educational experience.

Keywords: Advanced Materials Characterization, Big Data Integration, Data Analysis and Interpretation, Predictive Modeling, Real-world Applications.