Class Data Life Cycle and e-Health: Pipeline and Content

The curricular unit has as key goals the acquisition of basic knowledge about data processing, storage in cloud, and the role of data in e-health. To achieve these goals, the program addresses various programmatic content, including the lifecycle of data, artificial intelligence and learning of machines, data types, and learning methods applied to e-health data. In addition, students will explore how to transform data into knowledge, learn about data repositories, and discuss ethical issues, data protection and metadata, with a special focus on the context of e-health.

Not applicable

PC1. Data life cycle PC2. Artificial intelligence and machine learning PC3. Types of Data PC4. Learning methods and algorithms on e-health data PC5. From data to knowledge PC6. Data repositories PC7. Ethical issues related to data PC8. Data protection PC9. Metadata PC10. Data lifespan in e-health

The classes will be based in different teaching methods, from expository method to demonstrative method in some of the programme contents. The teaching on the data flow concept will be based on several use cases in the field of the digitalization of companies, the data flow in e-health and human resource management. Experienced professionals from the field of health, industry, recruitment, and development will be invited to share their experiences in specific topics of this unit.

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