Advanced Data Analysis for Healthcare using Python

Course Introduction 

This course is designed for healthcare professionals, researchers, and data analysts aiming to enhance their data analysis skills using Python. Participants will explore advanced techniques in statistical analysis, machine learning, and data visualization, with a specific focus on applications in the healthcare domain. 

Duration: 10 Days 

Course Objectives: 

1. Develop advanced proficiency in Python programming for healthcare data analysis. 

2. Explore statistical analysis techniques tailored for healthcare research. 

3. Implement machine learning models for predictive analytics in healthcare. 

4. Master data visualization tools and techniques for healthcare datasets. 

Course Modules: 

Module 1: Python Fundamentals for Healthcare Data Analysis 

• Review of Python basics. 

• Introduction to libraries (NumPy, Pandas) for data manipulation. 

• Hands-on exercises with healthcare datasets. 

Module 2: Advanced Statistical Analysis with Python 

• Implementing statistical tests using Python. 

• Exploratory data analysis (EDA) techniques for healthcare datasets. 

• Practical applications in healthcare research. 

Module 3: Machine Learning Basics with Scikit-Learn 

• Overview of machine learning in Python. 

• Introduction to Scikit-Learn for healthcare applications. 

• Building and evaluating machine learning models. 

Module 4: Predictive Modelling in Healthcare with Python 

• Feature engineering for healthcare data. 

• Developing predictive models using Python. 

• Tuning and optimizing machine learning models. 

Module 5: Data Visualization for Healthcare Analysis with Matplotlib and Seaborn 

• Creating impactful visualizations for healthcare data. 

• Interactive visualizations with Plotly. 

• Design principles for effective data communication in healthcare.