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Course Outline
Introduction to AI in Healthcare
- Overview of AI applications in healthcare
- Setting up Google Colab for healthcare AI projects
- Understanding key healthcare datasets
AI for Predictive Modeling in Healthcare
- Exploring healthcare predictive models
- Building predictive models using machine learning
- Evaluating healthcare data models
Medical Image Analysis with AI
- Introduction to AI for medical imaging
- Implementing deep learning models for image analysis
- Using AI to detect patterns in medical images
Data Preprocessing and Feature Engineering
- Cleaning and preparing healthcare data
- Feature engineering techniques for healthcare datasets
- Dealing with missing and unstructured data
Ethical Considerations in AI for Healthcare
- Understanding the ethical impact of AI in healthcare
- Ensuring privacy and data protection
- Fairness and transparency in AI models
AI-Powered Healthcare Case Studies
- Real-world AI applications in healthcare
- Case studies on AI-driven predictive analytics
- Medical image analysis with AI in clinical settings
Advanced AI Techniques in Healthcare
- Implementing advanced AI models
- Exploring natural language processing in healthcare
- AI-driven decision support systems in healthcare
Summary and Next Steps
Requirements
- Basic knowledge of AI and machine learning concepts
- Familiarity with Python programming
- Understanding of healthcare industry fundamentals
Audience
- Data scientists working in healthcare
- Healthcare professionals interested in AI
- Researchers exploring AI-driven healthcare solutions
14 Hours
Testimonials (4)
very friendly and helpful
Aktar Hossain - Unit4
Course - Building Microservices with Microsoft Azure Service Fabric (ASF)
The manual serverless setup. Also, I had no Idea sls web console exits, which is nice.
Rafał Kucharski - The Software House sp. z o.o.
Course - Serverless Framework for Developers
All good, nothing to improve
Ievgen Vinchyk - GE Medical Systems Polska Sp. Z O.O.
Course - AWS Lambda for Developers
IOT applications