🎓 Course Modules:
🧠 Module 1: Introduction to AI in Healthcare
Overview of healthcare challenges and opportunities
AI’s role in medical systems and hospital workflows
Regulatory frameworks (HIPAA, GDPR, FDA)
🏥 Module 2: Electronic Health Records (EHR) & Data Handling
EHR structure and clinical data types
Data cleaning and preprocessing techniques
Patient privacy and anonymization
🧪 Module 3: Predictive Analytics in Medicine
Disease prediction using machine learning
Risk scoring and early diagnosis
Case study: Diabetes and heart disease forecasting
🧬 Module 4: Medical Imaging & Computer Vision
Image classification and segmentation in radiology
Detecting tumors, fractures, and anomalies
Tools: OpenCV, PyTorch, TensorFlow in medical imaging
🔍 Module 5: Natural Language Processing in Healthcare
Analyzing clinical notes and prescriptions
Named Entity Recognition for symptoms, drugs, and conditions
NLP tools: spaCy, BERT for healthcare
🤖 Module 6: AI-Powered Robotics & Assistive Tech
Surgical robots and AI-assisted procedures
Wearable AI for patient monitoring
Rehabilitation and elderly care innovations
🧰 Module 7: Tools and Platforms for Healthcare AI
Google Health, IBM Watson, and open datasets
Building models with Scikit-learn and TensorFlow
Integrating AI into hospital systems
⚖️ Module 8: Ethics, Bias, and Fairness in Medical AI
Avoiding bias in clinical algorithms
Informed consent and explainable AI
Equity in AI access and treatment delivery
🧪 Module 9: AI in Drug Discovery & Genomics
Machine learning for molecule prediction
AI in vaccine and treatment development
Genomic data analysis and precision medicine
✅ Module 10: Final Capstone Project
Choose from projects like:
AI diagnosis system for X-rays
Predictive model for patient readmission
NLP-based medical chatbot
Final review and healthcare impact report
🧠Master Study NLP Fundamentals: The Foundation of Language Understanding in AI
📚Shop our library of over one million titles and learn anytime
👩🏫 Learn with our expert tutors
