Udemy MOOC / Non-credit 0

Python for Biostatistics: Analyzing Infectious Diseases Data

Name: Python for Biostatistics: Analyzing Infectious Diseases Data
Price: 29.99 USD
Availability: InStock

About this course

Welcome to Python for Biostatistics: Analyzing Infectious Diseases Data course. This is a comprehensive project-based course where you will learn step by step on how to perform complex analysis and visualization on infectious diseases datasets. This course is a perfect combination between biostatistics and Python, equipping you with the tools and techniques to tackle real-world challenges in public health. The course will be mainly concentrating on three major aspects, the first one is data analysis where you will explore the infectious diseases data from multiple perspectives, the second one is time series forecasting where you will be guided step by step on how to forecast the spread of infectious diseases using STL model, and the third one is public health policy where you will learn how to make a data driven public health policy based on epidemiological modeling. In the introduction session, you will learn the basic fundamentals of biostatistics, such as getting to know more about challenges that we commonly face when analyzing biostatistics data and statistical models that we will use, for instance STL which stands for seasonal trend decomposition. Then, you will continue by learning how to calculate infectious disease transmission using Kermack-McKendrick equation, this is a very important concept that you need to understand before getting into the coding session. Afterward, you will also learn several factors that can potentially accelerate the spread of infectious diseases, such as population density, healthcare accessibility, and antigenic variation. Once you have learnt all necessary information about biostatistics, we will start the project. Firstly, you will be guided step by step on how to set up Google Colab IDE. Not only that, you will also learn how to find and download infectious diseases dataset from Kaggle. Once, everything is ready, we will enter the main section of the course which is the project section The project will be consisted of three main parts, the first part is to conduct explor

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What you'll learn

data analysis techniques for infectious diseases
time series forecasting using the STL model
creating public health policies based on data analysis
understanding key biostatistics concepts
using Python in data analysis

Course objectives

to equip students with biostatistical analysis skills
to enhance proficiency in Python for data handling
to develop skills for forecasting disease spread
to guide students in formulating public health policies using data

Data Analysis Public Health #python #data visualization #epidemiology #data analysis #time series forecasting #google colab #data-driven decisions #public health policy #infectious diseases #biostatistics #Kermack-McKendrick equation

$29.99

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