R Programming Course - Classroom
2.250,00 EUR
- 22 hours
Unlock the power of data with R programming, one of the most widely used languages in data science and analytics. This hands-on course is designed to help you analyze, visualize, and interpret data using R’s powerful statistical and graphical capabilities. From core programming concepts to advanced data manipulation and analysis techniques, you’ll gain the skills needed to turn raw data into meaningful insights.
Key Features
Language
Course material in English
Level
Beginner - advanced structured curriculum
22 hours of instructor-led live training
50+ hours recommended study time
16+ hours of hands-on practice with R
8 hours of quizzes, assignments, and assessments
3 real-world projects for applied learning
Hands-on coding with real datasets
Expert mentorship and feedback
Industry-relevant curriculum aligned with data science needs
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Program completion certification included
Learning Outcomes
At the end of this program, you will be able to:
R Fundamentals
Set up RStudio and learn the basics of R, including syntax, variables, and data types.
Data Structures
Understand how to work with R data structures such as lists, vectors, and other data formats, and learn how to manipulate them effectively.
Control Flow
Use conditional statements and loops to build efficient and logical programs.
Object-Oriented Programming
Develop user-defined functions and apply object-oriented concepts like classes and objects in R.
Functions and Packages
Learn how to use built-in functions and integrate external packages for data analysis.
Data Querying and Filtering
Apply data processing techniques to filter, transform, and analyze datasets.
Data Summarization
Summarize and interpret data to support deeper analysis and decision-making.
Course timeline
Introduction to R Programming
Lesson 1
- Overview of R and its applications
- Why R is widely used in data science
Installing and Loading Libraries
Lesson 2
- Installing R and RStudio
- Managing and loading libraries
- Overview of commonly used packages
Data Structures in R
Lesson 3
- Vectors, lists, arrays, matrices
- Factors, strings, and data frames
- Writing code to manipulate data structures
Control & Loop Statements
Lesson 4
- Conditional statements (if, if-else, switch)
- Loops (for, while, repeat)
- Break and next statements
Functions in R
Lesson 5
- Writing custom functions
- Nested functions and arguments
- Calling functions effectively
Loop Functions
Lesson 6
- apply, lapply, sapply, mapply, tapply
- Efficient data operations using functional programming
String Manipulation & Regular Expressions
Lesson 7
- Working with strings and text data
- Pattern matching using regex functions
Working with Data in R
Lesson 8
- Reading and writing data files
- Connecting to databases
- Data manipulation and analysis techniques
Who Should Enroll in this Program?
Prerequisites
No prior requirements are needed. Basic programming knowledge is helpful.
Aspiring data scientists and analysts
Beginners looking to learn R from scratch
Software or data engineers exploring data analytics
Professionals interested in data-driven decision-making
Statements
Licensing and accreditation
The course is offered according to Partner Program Agreement and complies with the License Agreement requirements.
Equity Policy
Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.
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