Johns Hopkins University 3 credits Information Systems Engineering
This graduate-level course immerses students in the fast-evolving world of data engineering for artificial intelligence, focusing on the design and deployment of scalable, secure, and intelligent data ecosystems. Students will master the end-to-end data pipeline—from smart data ingestion and preprocessing to cloud-native storage, real-time integration, and privacy-enhancing technologies—within AI and machine learning frameworks. Leveraging cutting-edge cloud platforms such as AWS, Azure, and Google Cloud, participants will gain hands-on experience with industry-standard tools for data wrangling, visualization, and operationalization. The course emphasizes high-impact applications in fintech and biotech, while addressing critical issues in ethical AI, cybersecurity, and responsible data governance. Designed for future data scientists, AI engineers, and tech innovators, this course requires foundational knowledge in AI, programming, and machine learning. Prerequisite(s): EN.635.601 Foundation of Information Systems Engineering. Prior experience with databases, SQL, and Python is recommended.
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