What you'll learn
·
Data Science project
applied on COVID 19 data, understanding spread of the virus
·
Data Science best
practices from industry with full project walkthrough from setting up a project
to delivery
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Python with machine
learning, plotly, Facebook Prophet, dynamic dash-boards, SIR epidemic
simulations, Tableau Dashboards
Requirements
·
Python basics
·
Math basics
Description
The goal of this lecture is to transport the best practices of
data science from the industry while developing a COVID-19 analysis prototype
The student should learn the process of modeling (Python) and a
methodology to approach a business problem.
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, + bonus section Tableau
For this, we will follow an industry-standard 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)
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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)
Who this course is for:
·
Beginner data science
·
Practitioners with basic understanding of Python
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