bigdataanahealth
21 小时 通常来说是3天，包括中间休息。
大数据分析涉及检查大量不同数据集的过程，以便发现相关性，隐藏模式和其他有用的见解。
健康产业拥有大量复杂的异构医学和临床数据。对健康数据应用大数据分析在获得改善医疗保健服务的见解方面具有巨大潜力。然而，这些数据集的巨大性给分析和临床环境的实际应用带来了巨大挑战。
在这个以讲师为主导的现场培训（远程）中，参与者将学习如何在健康状况下进行大数据分析，因为他们将逐步进行一系列动手实践练习。
在培训结束时，参与者将能够：
听众
课程格式
注意
Machine Translated
Introduction to Big Data Analytics in Health
Overview of Big Data Analytics Technologies
Installing and Configuring Apache Hadoop MapReduce
Installing and Configuring Apache Spark
Using Predictive Modeling for Health Data
Using Apache Hadoop MapReduce for Health Data
Performing Phenotyping & Clustering on Health Data
Using Apache Spark for Health Data
Working with Medical Ontology
Using Graph Analysis on Health Data
Dimensionality Reduction on Health Data
Working with Patient Similarity Metrics
Troubleshooting
Summary and Conclusion
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