Learn Python for healthcare statistics

Course Overview

Introduction to Google Colab for healthcare statistics.
Introduction to Python.
Getting Google Colab files from Github (for this series of videos).
Pandas tutorial for beginners.
Summary statistics using python.
Plotly tutorial.
Sampling distributions.
Hypothesis testing tutorial using Python in Google Colab.
Design Matrices using Patsy in Python.
Linear models using the F distribution in python.
Ordinary Least Squares Tutorial using Python.

(Please note that we obtained the following content based on information that users may want to know, such as skills, applicable scenarios, future development, etc., combined with AI tools, and have been manually reviewed)
Learners can learn the following from this course:

1. Introduction to Python and Google Colab: Learners will gain an understanding of the basics of Python and how to use Google Colab to run Python code.

2. Essential Python Packages: Learners will learn how to use the essential Python packages, such as Pandas, to analyze data. They will also review summary statistics, explore plotting with Plotly, and understand sampling distributions.

3. Hypothesis Testing and Predictive Analytics: Learners will learn how to use hypothesis testing, design matrices, linear models, and Ordinary Least Squares to make predictions.

4. Application to Healthcare: Learners will gain the knowledge and skills to apply the Python analytical library to their roles in healthcare.

[Applications]
Learners will be able to apply the Python analytical library to their roles in healthcare. They will be able to use Python to obtain files from Github, review summary statistics, explore plotting with Plotly, understand sampling distributions, and learn hypothesis testing, design matrices, linear models, and Ordinary Least Squares. Additionally, learners will be able to use the Google Colab environment to create and run Python scripts.

[Career Paths]
1. Data Scientist: Data Scientists use Python to analyze large datasets and uncover trends and insights. They use predictive analytics to develop models and algorithms that can be used to make decisions and predictions. Data Scientists must have a strong understanding of statistics, machine learning, and data visualization. As healthcare organizations increasingly rely on data-driven decisions, the demand for Data Scientists with Python skills is growing.

2. Machine Learning Engineer: Machine Learning Engineers use Python to develop and deploy machine learning models. They must have a strong understanding of algorithms, data structures, and software engineering. As healthcare organizations increasingly rely on machine learning to automate processes and make decisions, the demand for Machine Learning Engineers with Python skills is growing.

3. Healthcare Analytics Specialist: Healthcare Analytics Specialists use Python to analyze healthcare data and uncover trends and insights. They must have a strong understanding of statistics, data visualization, and machine learning. As healthcare organizations increasingly rely on data-driven decisions, the demand for Healthcare Analytics Specialists with Python skills is growing.

4. Clinical Data Analyst: Clinical Data Analysts use Python to analyze clinical data and uncover trends and insights. They must have a strong understanding of statistics, data visualization, and machine learning. As healthcare organizations increasingly rely on data-driven decisions, the demand for Clinical Data Analysts with Python skills is growing.