Python for Biostatistics: Analyzing Infectious Diseases Data Free Coupon

Forecast infectious disease rate, build epidemiological modelling, and map the spread of infectious disease with heatmap
0 (0 reviews) 1,114+ students
Instructor: Christ Raharja Published by: Prabhat Kumar Ravi (MOD) English

Course Description

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 exploratory data analysis, the second part is to build forecasting model to predict the spread of the diseases in the future using time series model, meanwhile the third part is to perform epidemiological modelling and use the result to develop a public health policy to slow down the spread of the infectious disease.

First of all, before getting into the course, we need to ask this question to ourselves: why should we learn biostatistics, particularly infectious diseases analysis? Well, there are many reasons why, firstly, if you are interested in working in the public health or healthcare industry, having biostatistics knowledge would be very beneficial and help you to level up your career. In addition to that, you will also learn a lot of valuable skill sets that can be implemented in other projects, for example, time series decomposition can be used to forecast stock, real estate, commodity, and cryptocurrency markets. Last but not least, this course will also train you to be a better public health policy maker as you will extensively learn how to make data driven decisions and take other external factors into consideration.

Below are things that you can expect to learn from this course:

  • Learn the basic fundamentals of biostatistics and infectious disease analysis

  • Learn how to calculate infectious disease transmission rate using SIR model

  • Learn several factors that accelerate the spread of infectious disease, such as population density, herd immunity, and antigenic variation

  • Learn how to find and download datasets from Kaggle

  • Learn how to clean dataset by removing missing rows and duplicate values

  • Learn how to detect potential outliers using Z score method

  • Learn how to find correlation between population and disease rate

  • Learn how to analyze infected patient demographics

  • Learn how to map infectious disease per county using heatmap

  • Learn how to analyze infectious disease yearly trend

  • Learn how to perform confidence interval analysis

  • Learn how to forecast infectious disease rate using time series decomposition model

  • Learn how to do epidemiological modeling using SIR model

  • Learn how to perform public health policy evaluation

Review: Our Opinion

Everything You Need to Know About Python for Biostatistics: Analyzing Infectious Diseases Data

This course is a comprehensive and well-structured introduction to Python for Biostatistics: Analyzing Infectious Diseases Data. The instructor, Christ Raharja, is a leading expert in the field with a wealth of experience in Development to share.

The course is well-structured and easy to follow, and the instructor does a great job of explaining complex concepts in a clear and concise way.

The course is divided into sections, each of which covers a different aspect related to Data Science. Each module contains a series of video lectures, readings, and hands-on exercises.

The instructor does a great job of explaining each topic in a clear and concise way. He/She also provides plenty of examples and exercises to help students learn the material.

One of the things I liked most about this course is that it is very practical. The instructor focuses on teaching students the skills and knowledge they need to succeed in the real world. He/She also provides students with access to a variety of resources, including templates, checklists, and cheat sheets.

Another thing I liked about this course is that it is offered on Udemy. Udemy is a great platform for taking online courses because it offers a lot of flexibility for students. Students can choose to take courses at their own pace, and they can access the course materials from anywhere with an internet connection.

Udemy also offers a variety of payment options, so students can find a plan that works for them. The course also has a very active community forum where students can ask questions and interact with each other. The instructor is also very responsive to student questions and feedback.

Overall, I highly recommend this course to anyone who is interested in learning Python for Biostatistics: Analyzing Infectious Diseases Data. It is a well-organized and informative course that will teach you the skills and knowledge you need to succeed.

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