Learn more about the academic programs we are delivering in Summer 2025. If you have any questions about part-time studies, please contact us.
The course would cover the basics of data preparation, including cleaning, transformation, and integration techniques, but with an emphasis on how these techniques differ for use in AI models. The course would also cover the different types of data commonly used in AI, such as structured, unstructured, and semi-structured data, and how to prepare each type for use in AI applications. In addition, the course would cover the governance of data in AI, including privacy laws, ethical considerations, and responsible AI practices. Students would learn about the importance of transparency, accountability, and explainability in AI models and how to ensure these qualities in the data preparation and governance process.