Recall and define key terms and concepts related to Machine Learning and Big Data in healthcare. Explain how different machine learning algorithms function and identify suitable use cases for healthcare analytics. Summarize the contribution of Big Data analytics to clinical decision-making and patient care optimization. Demonstrate the ability to preprocess, clean, and prepare healthcare datasets for machine learning analysis. Examine and interpret machine learning model results to determine accuracy and performance within healthcare data. Critically assess data privacy, ethical considerations, and compliance issues in AI-driven healthcare analytics. Create and present a basic predictive model or concept demonstrating the use of machine learning to enhance healthcare outcomes.

Basic understanding of healthcare data management and informatics. Familiarity with statistics and data analytics concepts is recommended but not mandatory

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Healthcare professionals seeking to transition into data analytics roles. Data analysts and IT professionals working in healthcare systems. Students and researchers in health informatics and computer science. Policy developers and administrators aiming to understand the implications of AI in healthcare.