Brief Introduction
Analysis of CORONA / COVID-19 virus data with Python: data handling, machine learning, visualisation, spread simulationsDescription
The goal of this lecture is to transport the best practices of data science from the industry while developing a CORONA / COVID-19 analysis prototype
The student should learn the process of modeling (Python) and a methodology to approach a business problem based on daily updated COVID 19 data sets
The final result will be a dynamic dashboard - which can be updated by one click - of COVID-19 data with filtered and calculated data sets like the current Doubling Rate of confirmed cases
Techniques used are REST Services, Python Pandas, scikit-learn, Facebook Prophet, Plotly, Dash, and SIR virus spread simulations + bonus section Tableau for visual analytics
For this, we will follow an industry-standard CRISP process by focusing on the iterative nature of agile development
Business understanding (what is our goal)
Data Understanding (where do we get data and cleaning of data)
Data Preparation (data transformation and visualization)
Modeling (Statistics, Machine Learning, and SIR Simulations on COVID Data)
Deployment (how to deliver results, dynamic dashboards in python and Tableau)
Requirements
- Requirements
- Python basics
- Math basics
Frank Kienle
4.6 Raiting
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Analysis of CORONA / COVID-19 virus data with Python: data handling, machine learning, visualisation, spread simulations Business understanding (what is our goal)...
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