SkillUp
Artificial Intelligence for Healthcare 专项课程
SkillUp

Artificial Intelligence for Healthcare 专项课程

Build the Future of Healthcare with AI. Learn to design, implement, and evaluate responsible AI solutions that improve patient outcomes

SkillUp
Ramesh Sannareddy

位教师:SkillUp

包含在 Coursera Plus

深入学习学科知识
中级 等级

推荐体验

12 周 完成
在 3 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识
中级 等级

推荐体验

12 周 完成
在 3 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Describe how to apply machine learning techniques to analyze healthcare data and solve clinical problems

  • Evaluate the effectiveness of AI models in healthcare contexts, including performance metrics, clinical validation, and ethical considerations

  • Develop predictive models for patient outcomes using supervised and unsupervised learning techniques

  • Design and implement neural networks for medical image analysis and clinical decision support systems

要了解的详细信息

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授课语言:英语(English)
最近已更新!

November 2025

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专业化 - 3门课程系列

Foundations of AI in Healthcare

Foundations of AI in Healthcare

第 1 门课程8小时

您将学到什么

  • Describe how AI and machine learning are transforming healthcare delivery, clinical workflows, and patient outcomes.

  • Explain ethical frameworks, regulations, and governance standards relevant to AI in healthcare.

  • Summarize common challenges and solutions related to bias, privacy, and integration in AI healthcare implementation.

  • Design and implement machine learning workflows tailored to healthcare datasets and requirements.

您将获得的技能

类别:Artificial Intelligence
类别:Artificial Intelligence and Machine Learning (AI/ML)
类别:Health Informatics
类别:Healthcare Industry Knowledge
类别:Clinical Research
类别:Clinical Informatics
类别:Data Analysis
Machine Learning for Medical Data

Machine Learning for Medical Data

第 2 门课程10小时

您将学到什么

  • Define supervised and unsupervised machine learning techniques used for healthcare datasets.

  • Apply preprocessing, feature engineering, and class-imbalance management techniques to real healthcare datasets.

  • Design and implement supervised learning models for disease prediction and clinical decision support tasks.

  • Evaluate model performance using precision-recall metrics, calibration, and external validation.

您将获得的技能

类别:Predictive Modeling
类别:Deep Learning
类别:Healthcare Ethics
类别:Machine Learning
类别:Data Processing
类别:Health Informatics
类别:Clinical Informatics
类别:Data Mining
类别:Machine Learning Methods
类别:Electronic Medical Record System
类别:Machine Learning Algorithms
类别:Statistical Machine Learning
类别:Data Analysis
AI Technologies in Healthcare

AI Technologies in Healthcare

第 3 门课程9小时

您将学到什么

  • Identify key AI technologies in healthcare, including NLP, generative AI, and computer vision.

  • Explain how advanced AI models process clinical text, patient data, and medical images.

  • Analyze healthcare datasets to design and evaluate AI models using guided Jupyter labs.

  • Create an integrated AI solution combining NLP, generative AI, and computer vision tools.

您将获得的技能

类别:Jupyter
类别:Health Information Management
类别:Data Analysis
类别:Multimodal Prompts
类别:Artificial Intelligence and Machine Learning (AI/ML)
类别:Decision Support Systems
类别:Health Systems

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位教师

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113 门课程368,013 名学生

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