Biostatistics with Python
Apply Python for biostatistics with hands-on biomedical and biotechnology projects
Created by Darko Medin
Explore how to apply Python to real-world biostatistics problems in biomedical and biotechnology fields. You'll learn to analyze and interpret data from areas like diabetes, cardiology, epidemiology, and genetics. Gain practical experience by working through hands-on projects that bridge theory and application.
Packt | Nov 2024 | 374 min
What You Will Learn
You'll start by learning core biostatistics concepts and Python basics, then move on to practical data cleaning and descriptive analysis. Step-by-step projects guide you through hypothesis testing, predictive modeling, and clinical study design. By working on real biomedical data, you'll build a strong, practical skillset.
Key Features
- Clean and describe biological data sets using Python for accurate analysis
- Apply hypothesis testing and effect size analysis to draw meaningful conclusions
- Build predictive models and perform meta-analyses for robust biomedical research
Target Audience
Designed for life science professionals, researchers, and aspiring biostatisticians who want to use Python for data analysis in biology or medicine. If you have a basic background in life sciences or medicine and want to confidently analyze complex data, this course will help you reach your goals.
