This course is designed to teach you the most practical data science techniques in R to find valuable data insights.
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R is an open source software environment for statistical computing and graphics and is very popular with data scientists. R is being used for data analysis, extracting and transforming data, fitting models, drawing inferences, making predictions, plotting, and reporting results. Learn how to use R basics, working with data frames, data reshaping, basic statistics, graphing, linear models, nonlinear models, clustering, and model diagnostics.
You Will Learn
- How to configure the RStudio environment and load R packages
- How to use R basics such as basic math, data types, vectors, and calling functions
- How to use advanced data structures such as data frames, lists, and matrices
- How to use R base graphics
- How to use R basic statistics, correlation, and co-variance
- How to use linear models such as simple linear regression, logistic regression
- How to use non-linear models such as decision trees and Random Forests
- How to apply clustering using K-means
- How to complete model diagnostics
Geared To
- Anyone interested in learning to use data science techniques to find insights in data and who has at least some statistical and programming experience.
Instructor
Deanne Larson
President, DM, CBIP
Larson & Associates
Deanne Larson is an active practitioner and academic focusing on business intelligence and data warehousing with over 20 years of experience. Dr. Larson completed her doctorate in management in information technology leadership. Her doctoral dissertation research focused on a grounded theory qualitative study on establishing enterprise data strategy. She holds project management professional (PMP) and certified business intelligence professional (CBIP) certifications. Larson attended AT&T Executive Training at the Harvard Business School in 2001, focusing on IT leadership. She is a regular contributor to TDWI publications and presents several times a year at conferences. Dr. Larson is associate faculty at American Public University and University of Phoenix in the United States.