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Foundations of Healthcare Data Analytics

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Foundations of Healthcare Data Analytics

Ramesh Sannareddy
SkillUp

位教师:Ramesh Sannareddy

包含在 Coursera Plus

深入了解一个主题并学习基础知识。
中级 等级

推荐体验

9 小时 完成
灵活的计划
自行安排学习进度
深入了解一个主题并学习基础知识。
中级 等级

推荐体验

9 小时 完成
灵活的计划
自行安排学习进度

您将学到什么

  • Describe the types and sources of healthcare data, including electronic health records, claims data, and clinical trial data.

  • Explain data privacy regulations (HIPAA) and best practices for secure healthcare data handling.

  • Apply data collection and cleaning techniques specific to healthcare datasets using Python, Excel, and SQL.

  • Generate descriptive statistics and data quality reports by integrating, cleaning, and validating healthcare data.

要了解的详细信息

可分享的证书

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授课语言:英语(English)

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

该课程共有4个模块

In this module, you will learn about the fundamentals of healthcare data. The module begins with an overview of key data types, including electronic health records (EHRs), claims, registries, and clinical research data, and how they support decision-making and analytics across healthcare settings. You will explore healthcare data standards and classification systems, such as ICD, CPT, HL7, and FHIR, which ensure interoperability across systems. Through real-world examples, you will see how healthcare data flows from hospitals and clinics to research databases, enabling clinical, operational, and analytical insights. The module concludes with a discussion on how structured, standardized, and well-managed data contributes to improved patient care, efficient healthcare operations, and effective evidence-based decision-making.

涵盖的内容

6个视频4篇阅读材料4个作业1个讨论话题5个插件

In this module, you will learn how to safeguard sensitive healthcare data. The module begins with an exploration of privacy, security, and compliance requirements, emphasizing the importance of ethical data handling and patient protection. You will examine global regulations, including HIPAA and GDPR, and understand their impact on healthcare operations. The module introduces practical data protection strategies such as encryption, anonymization, and access control, illustrated through real-world examples of data breaches and prevention measures. Through hands-on labs, you will apply these principles to securely manage healthcare data, maintain regulatory compliance, and build trust and accountability in healthcare analytics and decision-making.

涵盖的内容

6个视频1篇阅读材料4个作业1个讨论话题3个插件

In this module, you will learn the technical skills needed to collect, organize, and prepare healthcare data for analysis. The module begins with importing data from multiple sources and building relational databases using Excel and SQL. You will practice essential data management techniques, including validation, cleaning, transformation, and standardization, to ensure data consistency and quality. Through real-world exercises, you will learn how to convert raw, inconsistent healthcare datasets into structured, reliable formats. By the end of this module, you will be able to prepare data that supports accurate reporting and evidence-based decision-making in healthcare.

涵盖的内容

6个视频3篇阅读材料4个作业3个插件

This module consolidates the knowledge and skills acquired throughout the course, guiding learners through a comprehensive, hands-on healthcare data analytics project. You will apply your understanding of healthcare data sources, privacy regulations, and data management techniques to solve a real-world healthcare analytics challenge. You will work with authentic healthcare datasets, demonstrating your ability to collect, clean, integrate, and analyze data while maintaining HIPAA compliance and ensuring data quality standards. Through structured problem-solving, you will demonstrate your competence in using Excel and SQL to generate meaningful insights from healthcare data, preparing yourself for entry-level roles in healthcare analytics.

涵盖的内容

1个视频2篇阅读材料1个作业1次同伴评审1个讨论话题2个插件

位教师

Ramesh Sannareddy
21 门课程479,785 名学生

提供方

SkillUp

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