Data Analytics V: Python and R

In this course, students will expand on skills acquired in the prior courses by learning how to combine R and Python capability into one project using R Studio and Anaconda. Students will develop a working Notebook using R Markdown and transfer results into an interactive web-based dashboard using Shiny.

At the end of the course, student will know:

1.    How to use Python and R together to efficiently perform data analysis.
2.    How to import data sets from different repositories.
3.    How to create a workflow using R Markdown to maintain data analytics projects and communicate results to stakeholders.
4.    How to develop an interactive web-based dashboard using Shiny.

Consider 3-hour lecture per week, and 4-6 hours per week on quizzes and ongoing real-world projects for homework.

Who Is This Course For? 

for those considering a professional career in Data Analytics field

What Will You Learn? 
how to combine R and Python capability into one project using R Studio and Anaconda
developing a workflow using R Markdown to maintain data analytics projects and communicate results to stakeholders.
developing an interactive web-based dashboard using Shiny.
Mentor(s) 

Cynthia V. Marcello

Cynthia V. Marcello, DM is a tech solopreneur, software applications developer, data scientist, and business management consultant with 25 years of experience working with small-to-medium businesses, corporations, government, and educational agencies. She has developed data-driven applications for the Department of Defense (logistics), and numerous custom software applications (front-end and back-end) for operations and enterprise materials handling processes of corporations, and order-entry and production systems for online retailers.

Duration 
5 weeks
Cost 
$499.00
Bootcamp 
Data Analytics Bootcamp

Course Schedule:

Starting Wednesday, June 9, 2021 - 6:00pm
Location:
online
146 3rd Street
Newburgh, NY 12550
This course is part of a bootcamp: Data Analytics Bootcamp
All class dates:
Jun 9, Jun 16, Jun 23, Jun 30, Jul 7