Practical Data Science with R (PDSwR) is the course to start with if you are starting as a data scientist or aspire to be one. If you already practice data science, PDSwR will fill in knowledge gaps and even give you a new perspective on the technologies you now employ.
This course covers data science, a discipline that builds predictive models using findings from machine learning, statistics, and computer science.
Critical business data is being gathered, curated, examined, and reported more frequently by business analysts and engineers. Without much academic theory or complex mathematics, one can efficiently complete daily Data Science work using the R language and its companion tools.
You can learn how to use the R programming language and practical statistical approaches in ordinary business circumstances with the help of experimental data science with R training. It demonstrates how to conduct experiments (such as A/B testing), create prediction models, and deliver results to audiences of different levels using examples from business intelligence, marketing, and decision support.
a. The data science process
b. Loading data into R
c. Exploring data
d. Managing data
a. Choosing and evaluating models
b. Memorization methods
c. Linear and logistic regression
d. Unsupervised methods
e. Exploring advanced methods
a. Documentation and deployment
b. Producing effective presentations
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