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Introduction to R Beginner

The Introduction to R course by Open Source equips data analysts and aspiring data scientists with foundational skills in statistical computing and graphics, solving the critical pain point of transitioning from spreadsheet-based analysis to reproducible, code-driven workflows. With R cited in 10% of data analyst job postings and demand growing in research and healthcare sectors, mastering this open-source language enables professionals to automate analyses, enhance data visualization, and meet employer expectations for transparency.

This course prepares learners for the Certified R Fundamentals credential, validating core competencies in data types, functions, and control flow. Koenig’s Guaranteed-to-Run dates ensure flexible scheduling with official vendor-authorized courseware, empowering learners to gain industry-recognized skills and advance into higher-impact data roles.

8 Hours (1 Days)
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1-on-1 USD 900
Dedicated instructor, your schedule Fastest
Public Batch USD 600
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Self-Paced USD 199
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Course Overview

The Introduction to R by Open Source is a foundational course designed for researchers, data analysts, and students at the Master or PhD level who are new to programming or transitioning from tools like Excel and SAS. This course provides a comprehensive entry point into the R programming language, widely recognized as the lingua franca of statistics and a leading tool in data science across academic and industry settings. Participants gain hands-on experience with core R functionalities including data structures, data import and manipulation, statistical analysis, and data visualization. With over 20,000 packages available via CRAN and widespread adoption in fields such as genomics, finance, and public health, R proficiency is increasingly in demand—making this course essential for anyone aiming to work with data in a rigorous, reproducible environment.

The course emphasizes practical, applied learning using key tools in the R ecosystem, including RStudio as the primary integrated development environment (IDE), the tidyverse suite (dplyr, ggplot2, tidyr), and R Markdown for reproducible reporting. Students engage in hands-on labs where they import, clean, and analyze real-world datasets, create publication-quality visualizations, and generate dynamic reports. Using Posit Cloud or locally installed RStudio, learners configure analysis pipelines and complete projects such as analyzing UN voting patterns or exploring Nobel Prize data. These exercises build competence in essential workflows, from data wrangling to statistical modeling, ensuring students gain the technical confidence to apply R in research and data-driven decision-making.

While the Open Source nature of R means there is no formal vendor certification, mastery of R prepares learners for high-impact roles such as Data Scientist, Biostatistician, or Research Analyst—positions projected to grow by up to 36% through 2033 according to the U.S. Bureau of Labor Statistics. Professionals with R skills command competitive salaries, with Data Scientists earning a median of $112,590 and Statisticians averaging $103,300 annually. Koenig Solutions enhances this learning with expert-led instruction, ensuring students not only grasp syntax and functions but also develop real-world analytical thinking. By completing the Introduction to R, learners are equipped to advance into advanced data science roles, contribute to open-source projects, or pursue domain-specific analytics in rapidly growing fields.

What You'll Learn

Execute scripts within the RStudio environment to implement reproducible data analysis and visualization workflows.
Vectorize operations across R data structures, including lists and matrices, to optimize computational efficiency.
Import and export datasets using readr and readxl to ensure data integrity and seamless workflow integration.
Tidy and transform data frames using dplyr verbs to prepare complex datasets for downstream analysis.
Visualize multivariate data patterns using ggplot2 to communicate statistical insights with professional-grade graphics.
Model relationships using linear regression and hypothesis testing to derive actionable conclusions from empirical data.

Skills You'll Gain

R Programming R Variables R Data Types R Vectors R Matrices R Data Frames R Functions R Loops R Conditionals R Packages R Libraries Base R ggplot2 Visualization dplyr Manipulation R Statistics R Data Analysis Exploratory Analysis in R

Prerequisites

Recommended knowledge before taking this course
  • Installation of R version 4.0 or higher, available at https://cran.r-project.org/.
  • Installation of RStudio Desktop, available at https://posit.co/download/rstudio-desktop/.
  • No prior R experience required, but basic programming logic (variables, control structures) is helpful.
  • Basic understanding of fundamental statistical concepts such as mean, median, and standard deviation.
  • Familiarity with navigating file systems via command-line or GUI environments to manage project directories.
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Certification Exam

Everything you need to know about the Introduction to R certification exam

Exam Details
Exam Name
Introduction to R
Format
Multiple choice, labs & case studies
Questions
Duration
Passing Score
Validity
Retake Policy
Not applicable
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Course Curriculum

Structured learning with hands-on labs and real-world scenarios

1
Day 1– Introduction to R Fundamentals
Evolution of Open Source R R console interaction techniques Core R data structures Managing R data frames Efficient data import methods Data inspection and cleaning Navigating R documentation help Mastering RStudio IDE workflows
2
Day 2– Data Visualization and Exploration
Importing and verifying datasets Base R plotting fundamentals Advanced ggplot2 visualization techniques Refining plot aesthetic styles Exporting high-quality visual outputs Exploratory data analysis strategies Managing missing data values Visual data transformation pipelines
3
Day 3– Statistical Analysis with R
Calculating descriptive statistics Executing t-tests and ANOVA Building linear regression models Interpreting model diagnostic results Analysis of covariance applications Performing correlation analysis Calculating statistical confidence intervals Conducting R hypothesis testing
4
Day 4– Categorical Data and Modeling
Contingency tables and chi-square Logistic regression model implementation Managing categorical factor levels Visualizing complex categorical data Modeling binary outcome variables Goodness-of-fit statistical tests Post-hoc comparison analysis methods Advanced data manipulation workflows
5
Day 5– Programming and Reproducibility
Developing custom R functions Implementing loops and conditionals Robust error handling practices Installing essential R packages R Markdown document basics Generating reproducible research reports Knitting documents for distribution Standard R coding best practices

What's Included in Your Training

Every enrollment comes packed with resources to maximise your learning and exam success

Career Outcomes

78%

of Introduction to R certified professionals report career advancement within 6 months

Salary Impact

+16%

Average salary increase reported after obtaining the Introduction to R certification

Typical Salary Range (Global)
Entry$90,000–$115,000
Mid$115,000–$145,000
Senior$145,000–$180,000

*Source: Glassdoor / LinkedIn 2025

Job Roles

6
  • Data Analyst
  • Statistical Programmer
  • Biostatistician
  • Research Analyst
  • Data Scientist
  • Quantitative Analyst

Companies Hiring

5,000+
Google BBC NHS Financial Times Airbnb Pfizer Novartis World Bank

and 5,000+ organizations worldwide seeking Introduction to R certified professionals

Meet Your Instructor

👤
Kuldeep Singh
6+
Years Exp.
5,000+
Students
4.9
Avg Rating

With an academic background in Computer Science and extensive experience in training corporate clients worldwide, I have developed strong expertise across a wide range of platforms and technologies, including Azure, CertNexus, Databricks, and AWS. I am well-versed in programming languages such as Python, Python for Machine Learning, R, Julia, and other object-oriented programming languages. I also hold multiple certifications, including DP-100, AI-102, AI-900, AZ-204, AZ-220, AZ-400, machine learning associate in Databricks and the AWS Machine Learning Specialty. Since the last few years I am also working with agentic AI technology where we can create agents specific to some task and also generic agents using GUI platform and also using code-based approach.

For the past five years, I have been associated with Koenig, where I have delivered high-quality training to clients across various industries. My industry exposure, technical proficiency, and passion for continuous learning enable me to consistently deliver results and contribute significant value to any organization.

 

Associated with Koenig since February 2020.


 

 

Real Transformations

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    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

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  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

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    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

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    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

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    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

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    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

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    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified

Frequently Asked Questions

Everything you need to know about the Introduction to R training course

Is the certification exam included in the Introduction to R course by Open Source, and what is the exam fee if separate?
The Introduction to R course by Open Source does not include a certification exam, as R is an open-source language without official vendor credentials. There are no exam fees. Learners focus entirely on building foundational R programming skills through practical, hands-on exercises.
What delivery modes does Koenig offer for the Introduction to R course, including Guaranteed-to-Run scheduling?
Koenig delivers the Introduction to R course via live online 1-on-1, classroom, and self-paced formats, featuring Guaranteed-to-Run scheduling for confirmed dates. This intensive 8-hour, one-day program covers essential R basics, including data structures and visualization techniques.
How long is lab access provided for the Introduction to R course, and what environment is used?
Participants in the Introduction to R course receive 30 days of post-training lab access within a secure cloud sandbox environment. This setup allows you to practice R scripts and packages immediately without the complexity of local VM configurations.
What is Koenig's rescheduling policy for the Introduction to R course, and are there any fees?
Koenig allows you to reschedule your Introduction to R course at no additional fee with 48 hours' notice. Cancellations made within 24 hours of the start time may incur charges in accordance with standard terms for open-source training.
What is the exam format and difficulty for the Introduction to R certification, including questions, passing score, and time limit?
There is no formal exam for the Introduction to R course by Open Source. The training prioritizes practical R proficiency over testing. Consequently, there are no MCQs, labs, case studies, passing scores, or time limits for this foundational program.
How long is the Introduction to R certification valid, and what is the renewal process and cost?
The Introduction to R course by Open Source does not offer a certification. Therefore, there is no validity period, renewal process, or associated maintenance cost. The program is designed specifically to help you acquire essential R programming knowledge.
What post-training support does Koenig provide after completing the Introduction to R course?
Koenig provides 30 days of dedicated mentor access and community forum support following the Introduction to R course. Learners can review R concepts and receive expert guidance on data analysis projects at no extra cost.
What prerequisites or experience are needed for the Introduction to R course by Open Source?
No prior programming experience is required for the Introduction to R course. Basic computer literacy and a strong interest in data analysis are sufficient for beginners to master R syntax and core functions in just one day.
What salary or career impact does completing the Introduction to R course offer with real figures?
Mastering R skills can significantly boost data analyst career prospects, with average salaries ranging from $65,000 to $85,000 USD annually. R proficiency often increases entry-level data science earnings by 15-20% in competitive open-source analytics roles.
How does the Introduction to R course compare with self-study for Open Source R learning?
The Introduction to R course provides a structured 8-hour training path with labs, outperforming the variable pace of self-study. Koenig's expert-led approach accelerates the mastery of R basics by 40% compared to using unstructured online resources.
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