Machine Learning and AI Applications in Healthcare

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Machine Learning and AI Applications in Healthcare

This course is part of Microsoft Azure AI in Healthcare Professional Certificate

Instructor: Microsoft

Included with

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Build and deploy machine learning models using healthcare datasets and Azure AI tools.
Create predictive analytics solutions for patient outcomes and clinical decision support.
Evaluate and interpret AI models to ensure fairness, reliability, and actionable insights in healthcare.

Skills you'll gain

Category: Predictive Modeling
Category: Machine Learning
Category: Health Equity
Category: Machine Learning Methods
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Model Evaluation
Category: Health Informatics
Category: Predictive Analytics
Category: MLOps (Machine Learning Operations)
Category: Data Visualization Software
Category: Dashboard Creation
Category: Medical Imaging
Category: Responsible AI
Category: Data Presentation
Category: Model Training
Category: Image Analysis

Tools you'll learn

Category: Power BI
Category: AI Workflows
Category: Microsoft Azure
Category: Model Deployment

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

18 assignments¹

AI Graded see disclaimer

Taught in English

Build your Machine Learning expertise

This course is part of the Microsoft Azure AI in Healthcare Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Microsoft

There are 4 modules in this course

This comprehensive course bridges machine learning fundamentals with specialized healthcare AI applications, guiding students through the complete AI model lifecycle from data preprocessing to production deployment. You'll master core ML algorithms and deep learning architectures while gaining hands-on experience building medical imaging analysis systems, predictive models for patient outcomes, and clinical NLP applications using Azure AI services including Azure Machine Learning, Cognitive Services, and Computer Vision. The curriculum emphasizes healthcare-specific challenges including rigorous clinical validation methodologies that satisfy regulatory requirements, comprehensive bias detection and mitigation strategies to ensure equitable performance across diverse patient populations, and secure HIPAA-compliant data handling practices. Through practical labs and real-world case studies, you'll develop skills in model training, hyperparameter optimization, performance evaluation using clinical metrics (sensitivity, specificity, AUC), MLOps implementation with CI/CD pipelines, and creating compelling data visualizations that communicate AI insights to clinical stakeholders.

This foundational module introduces learners to essential machine learning concepts specifically applied to healthcare contexts. Students explore the complete AI model lifecycle from initial data preparation through deployment, gaining hands-on experience with Azure ML Studio's visual interface. The module emphasizes practical application of ML fundamentals while establishing critical validation practices necessary for clinical environments.

What's included

6 videos6 readings4 assignments

6 videosTotal 19 minutes

Why Machine Learning Revolutionizes Healthcare2 minutes
Building Your First Healthcare ML Model in Azure3 minutes
From Data to Deployment: The Journey3 minutes
End-to-End Model Development in Azure ML4 minutes
When Models Fail: The Importance of Validation2 minutes
Advanced Validation Techniques in Azure ML4 minutes

6 readingsTotal 315 minutes

Machine Learning Essentials for Healthcare Professionals15 minutes
Hands-on – Readmission Risk Predictor Development90 minutes
The Complete Healthcare AI Model Lifecycle15 minutes
Hands-on – Complete Lifecycle Implementation90 minutes
Clinical Model Validation Strategies15 minutes
Hands-on – Multi-Site Validation Exercise90 minutes

4 assignmentsTotal 300 minutes

ML Fundamentals Mastery90 minutes
Lifecycle Management Proficiency90 minutes
Validation Excellence Assessment90 minutes
Machine Learning Foundations and Model Development30 minutes

This module addresses critical challenges in healthcare AI implementation by focusing on bias detection, system reliability, and model interpretability. Learners develop expertise in identifying and mitigating bias in healthcare datasets while implementing fairness constraints and reliability frameworks. The module emphasizes creating interpretable AI solutions that translate complex model outputs into clinically meaningful insights for healthcare professionals.

What's included

6 videos5 readings5 assignments

6 videosTotal 22 minutes

Hidden Bias, Real Consequences2 minutes
Detecting Bias with Azure Responsible AI Dashboard5 minutes
Building Trust Through Reliable AI2 minutes
Implementing Fairness Constraints in Azure ML5 minutes
Making Black Boxes Transparent2 minutes
Creating Interpretable Clinical AI with Azure5 minutes

5 readingsTotal 225 minutes

Sources and Impacts of Healthcare AI Bias15 minutes
Hands-on – Bias Detection Workshop90 minutes
Ensuring Healthcare AI Reliability15 minutes
Explainable AI for Clinical Decision-Making15 minutes
Hands-on – Clinical Explanation Design90 minutes

5 assignmentsTotal 390 minutes

Bias Identification and Assessment90 minutes
Reliability Engineering for Clinical AI90 minutes
Reliability and Fairness Implementation90 minutes
Interpretation and Translation Mastery90 minutes
AI Bias, Reliability, and Interpretability30 minutes

This module explores specialized applications of AI in medical imaging analysis and patient risk prediction. Students learn to implement computer vision solutions for diagnostic imaging support while developing sophisticated predictive models for clinical risk assessment. The module combines hands-on experience with Azure Cognitive Services and pre-built model libraries to create practical healthcare AI applications.

What's included

6 videos6 readings4 assignments

6 videosTotal 22 minutes

AI as the Radiologist's Assistant2 minutes
Building a Chest X-Ray Classifier with Azure5 minutes
Predicting the Unpredictable2 minutes
Developing a Readmission Risk Model in Azure ML5 minutes
Standing on the Shoulders of Giants2 minutes
Implementing Pre-Built Models from Azure AI Gallery5 minutes

6 readingsTotal 315 minutes

Medical Imaging AI Fundamentals15 minutes
Hands-on – Medical Image Analysis Pipeline90 minutes
Clinical Risk Prediction Modeling15 minutes
Hands-on – Comprehensive Risk Prediction System90 minutes
Leveraging Pre-Built Healthcare AI Models15 minutes
Hands-on – Model Library Evaluation and Selection90 minutes

4 assignmentsTotal 180 minutes

Medical Imaging AI Proficiency30 minutes
Risk Prediction Excellence90 minutes
Model Library Utilization30 minutes
Medical Imaging and Predictive Analytics30 minutes

This module focuses on transforming healthcare data and AI predictions into actionable visual insights for clinical decision-making. Learners master data integration techniques using Azure Synapse while creating comprehensive dashboards with Power BI. The module emphasizes building visualization solutions that effectively communicate complex healthcare analytics to diverse stakeholder audiences, from clinicians to administrators.

What's included

6 videos6 readings5 assignments

6 videosTotal 20 minutes

From Data Chaos to Clinical Insights2 minutes
Building a Healthcare Data Pipeline with Azure Synapse4 minutes
Seeing the Story in the Data2 minutes
Creating Clinical Dashboards with Power BI5 minutes
Predictive Analytics Meets Visual Intelligence2 minutes
Integrating ML Models with Power BI Dashboards4 minutes

6 readingsTotal 315 minutes

Healthcare Data Integration Strategies15 minutes
Hands-on – Multi-Source Data Integration Project90 minutes
Effective Healthcare Data Visualization15 minutes
Hands-on – Comprehensive Healthcare Dashboard Development90 minutes
Integrated Analytics and ML Visualization15 minutes
Hands-on – Predictive Analytics Dashboard Creation90 minutes

5 assignmentsTotal 210 minutes

Data Integration Mastery30 minutes
Visualization Excellence30 minutes
Advanced Analytics Integration30 minutes
Healthcare Data Visualization and Analytics30 minutes
Patient Risk Prediction and Visualization System90 minutes

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Instructor

Microsoft

421 Courses2,831,942 learners

Offered by

Microsoft

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.