Udemy course Data science on COVID-19 / CORONA virus spread data by Frank Kienle
Data science on COVID-19 / CORONA virus spread data is the best Udemy course on the market. With this offer they will be able to greatly improve their knowledge and become more competitive within the Development category. Therefore, if you are looking to improve your Development skills we recommend that you download Data science on COVID-19 / CORONA virus spread data udemy course.
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Course data:
- Author: Frank Kienle
- Course rating: 4.6
- Category: Development
- Modality: Online
- Status: Available
- Idiom: English
Abouth Frank Kienle
Frank Kienle worked for Blue Yonder from 01/2013 to 09/2017, first as a senior data scientist, later as director of data science consulting.
What the udemy Data science on COVID-19 / CORONA virus spread data course teaches?
What you’ll learn Analytics 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 Python with analysis, machine learning, visualisation, Facebook Prophet, SIR epidemic simulations, Tableau Dashboards
Analysis of CORONA / COVID-19 virus data with Python: data handling, machine learning, visualisation, spread simulations
More information about the course Data science on COVID-19 / CORONA virus spread data
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)
