Global Certificate in Data Analytics for Health Decisions
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⢠Data Acquisition & Management: This unit will cover techniques for collecting, cleaning, and managing data for use in health decision making. Topics may include data sources, data quality, and data management strategies.
⢠Statistical Analysis: This unit will cover fundamental statistical concepts and methods commonly used in data analytics for health decisions. Topics may include descriptive statistics, probability distributions, hypothesis testing, and regression analysis.
⢠Data Visualization: This unit will cover techniques for presenting data visually to aid in decision making. Topics may include chart types, data storytelling, and data communication best practices.
⢠Machine Learning: This unit will cover machine learning algorithms and techniques for predictive modeling in health decisions. Topics may include supervised and unsupervised learning, model evaluation, and model selection.
⢠Healthcare Systems & Policy: This unit will cover the healthcare system and policy landscape, including the challenges and opportunities for data-driven decision making. Topics may include healthcare financing, delivery systems, and policy interventions.
⢠Ethics & Privacy: This unit will cover ethical and privacy considerations in data analytics for health decisions. Topics may include informed consent, data security, and data sharing.
⢠Data Governance & Quality: This unit will cover the principles and practices of data governance and quality management in healthcare. Topics may include data standards, data stewardship, and data quality assurance.
⢠Project Management: This unit will cover the principles and practices of project management in data analytics for health decisions. Topics may include project planning, execution, and monitoring.
⢠Communication & Collaboration: This unit will cover effective communication and collaboration skills for data analytics in healthcare. Topics may include stakeholder management, teamwork, and cross-functional collaboration.
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