R Programming Instructor-led Training

Uplatz offers this comprehensive training on R Programming. The course will be conducted as instructor-led online classes.

R is a programming language and software environment for statistical analysis, graphics representation and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team.

R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac.

R is a powerful language for data analysis, data visualization, machine learning, statistics. Originally developed for statistical programming, it is now one of the most popular languages in data science.

In this R Programming online training, you will learn how to apply the R programming language to carry out essential data management, wrangling and processing activities. This course will cover all of the fundamentals of data processing and analysis in the R environment. Prepare, transform, and manage datasets and their variables, export/import data from various file formats (Excel spreadsheets, csv, tab, txt, etc.), create simple graphical representations of the data (bar plots, histograms, box plots, etc), obtain summaries, data aggregations, cross-tabulations, frequency and pivot tables, and run and explain results.

This R training will also expose you to data visualization tools available in R for data reporting and research communication, as well as modelling utilizing multiple linear regression approaches. The course will address current methods to practical data science utilizing R and its rich ecosystem of external libraries, including the tidyverse family of packages, such as dplyr, ggplot2, tidyr, readr, and tibble, as well as other vital R libraries for data wrangling and statistics.

In this R Programming course, you'll be starting with th basics of R, and you'll end with the confidence to start writing your own R scripts. But this isn't your typical textbook introduction to R. You're not just learning about R fundamentals, you'll be using R to solve problems related to movies data. Using a concrete example makes the learning painless.

You will learn about the fundamentals of R syntax, including assigning variables and doing simple operations with one of R's most important data structures -- vectors! From vectors, you'll then learn about lists, matrix, arrays and data frames. Then you'll jump into conditional statements, functions, classes and debugging. Once you've covered the basics - you'll learn about reading and writing data in R, whether it's a table format (CSV, Excel) or a text file (.txt). Finally, you'll end with some important functions for character strings and dates in R.

Course Outcomes

• Understand the fundamentals of R programming language
• Set up software for statistical programming.
• Use R's loop functions and debugging tools to your advantage
• Using R profiler, collect comprehensive data
• Write your own R code and programs
• Use R for data visualization and analysis

Uplatz Certificate of Completion

Digital certificate - Included

R Programming - Course Syllabus

Module 1 - R basics

• Math, Variables, and Strings
• Vectors and Factors
• Vector operations

Module 2 - Data structures in R

• Arrays & Matrices
• Lists
• Dataframes

Module 3 - R programming fundamentals

• Conditions and loops
• Functions in R
• Objects and Classes
• Debugging

Module 4 - Working with data in R

• Reading CSV and Excel Files
• Reading text files
• Writing and saving data objects to file in R

Module 5 - Strings and Dates in R

• String operations in R
• Regular Expressions
• Dates in R

Everyone

Passion and determination to achieve your goals!

• Software Engineer - R, Python
• R Programmer Analyst
• Data Analyst & Consultant
• Data Scientist
• Data Architect
• Application Developer
• Software Developer & Programmer
• Application Developer
• Business Analyst
• BI & Reporting Developer/Analyst
• IT Consultant
• Technical Lead
• Solution Architect
• Data Science Engineer - Machine Learning/R
• Machine Learning Engineer
• R Programming Application Developer

Currently there are no Q&As for this course. Be the first to ask a question.