R Introduction in Data Analytics
The accredited person is able to recognize the basic data analytics tools and techniques for extracting and manipulating information, applying the R programming language, different data analysis algorithms, and statistical and mathematical results in a practical and detailed manner.
Criteria
Autonomy: Apply judgment in a basic and generic way.
Influence: Share ideas with colleagues.
Complexity: Require guidance for the development of specific tasks.
Skill: Select the most appropriate tools and computational structures for data manipulation using the R software.
Skill: Identify the data analysis and visualization techniques in R that facilitate trend exploration and result presentation.
Course: To make use of 16 lecture hours and 29 hours of extracurricular work, for a total of 45 hours, equivalent to 1 academic costarrican credit.
Assessment: To pass the course with a final grade equal to or greater than 70.
SINT-900