Habilidades que obtendrás: R Programming, Statistical Programming, Computer Programming, Mathematics, Data Analysis, Data Visualization, Linear Algebra, ArcGIS, Computational Logic, Mathematical Theory & Analysis, Other Programming Languages, Plot (Graphics), Probability & Statistics, Theoretical Computer Science
Beginner · Course · 1-3 Months
Habilidades que obtendrás: Data Analysis, Business Analysis, Exploratory Data Analysis, Probability & Statistics, Data Visualization, R Programming, Statistical Programming, Financial Analysis
Intermediate · Specialization · 3-6 Months
Habilidades que obtendrás: Machine Learning, Data Management, Statistical Programming, Python Programming, Machine Learning Algorithms, Apache, Deep Learning, Machine Learning Software, Artificial Neural Networks, Probability & Statistics, Cloud Computing, Statistical Machine Learning, Extract, Transform, Load, Basic Descriptive Statistics, General Statistics, IBM Cloud, Data Model, Applied Machine Learning, Data Analysis, Data Visualization, Dimensionality Reduction, SQL, Statistical Visualization, Feature Engineering, Linear Algebra, Mathematics, Natural Language Processing, Tensorflow, Bayesian Network, Cloud Platforms, Cloud Storage, Computer Vision, Correlation And Dependence, Data Structures, Data Warehousing, Database Application, NoSQL, Plot (Graphics), Probability Distribution, R Programming, Regression, Algorithms, Bayesian Statistics, Big Data, Change Management, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis Software, Data Mining, Distributed Computing Architecture, Estimation, Exploratory Data Analysis, Internet Of Things, Leadership and Management, Programming Principles, Statistical Analysis, Strategy and Operations, Theoretical Computer Science
Advanced · Specialization · 3-6 Months
Habilidades que obtendrás: R Programming, Data Analysis, Statistical Programming, Data Science, General Statistics, Statistical Analysis, Probability & Statistics, Statistical Tests, Machine Learning, Exploratory Data Analysis, Basic Descriptive Statistics, Machine Learning Software, Linear Algebra, Bayesian Statistics, Correlation And Dependence, Econometrics, Estimation, Regression, Data Visualization Software, Software Visualization, Statistical Visualization, Probability Distribution, Theoretical Computer Science, Data Visualization, Interactive Data Visualization, Natural Language Processing, Plot (Graphics), Big Data, Computer Programming, Computer Programming Tools, Data Structures, Experiment, Machine Learning Algorithms, Software Engineering Tools, Spreadsheet Software, Algorithms, Application Development, Applied Machine Learning, Business Analysis, Data Management, Extract, Transform, Load, Knitr
Beginner · Specialization · 3-6 Months
Habilidades que obtendrás: Basic Descriptive Statistics, Correlation And Dependence, Data Analysis, Econometrics, Estimation, General Statistics, Linear Algebra, Probability & Statistics, R Programming, Regression, Statistical Analysis, Statistical Programming, Statistical Tests, Data Science, Probability Distribution, Business Analysis
Mixed · Course · 1-4 Weeks
Habilidades que obtendrás: Data Analysis, Data Mining, General Statistics, R Programming, Statistical Programming, Exploratory Data Analysis, Probability & Statistics, Statistical Analysis, Basic Descriptive Statistics, Statistical Tests, Plot (Graphics), Probability Distribution, Regression, Applied Machine Learning, Big Data, Data Structures, Deep Learning, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Statistical Machine Learning, Statistical Visualization, Advertising, Business Analysis, Communication, Data Science, Marketing
Intermediate · Course · 1-3 Months
R programming is the use of the R computer language for statistical analysis and graphic presentation. R is commonly used in business and research computing environments to analyze and visualize data, then create reports that can be used for decision making. R programming is increasingly more important given the expansion of big data for analysis.
It's important to learn R programming if you want to be able to build computer programs that wrangle data and convert it into usable information. Organizations often have large amounts of data but are unable to understand what it means. Using programs written by R, you can generate Bayesian statistics and graphic analysis for business analytics, public health, and medical research, among other industries. Learning R is a component of learning data science, so another reason to study R programming is to get some of the fundamentals completed before venturing deeper into computer science studies.
Typical careers that use R programming are in business analytics, financial services, and medical research. It is also a skill used in many data science roles. R programming pulls out information from large sets of data, so any field that calls for statistical inference from big data needs competent R programmers to create the analytics and reports needed. Some experience with R programming is useful for people who will be managing programming teams or requesting reports made from programs written in R. As big data analysis becomes more important in more fields, R programming becomes more valuable in the workplace.
Online courses can help you learn R programming by introducing the fundamentals of the language, teaching how it connects to such industries as finance and health care, and offering projects that let you show what you have learned. Courses are offered at all levels, from beginning to advanced. Many of them set you up for further work in data science or allow you to earn a specialization or certificate.