R Programming Basics for Data Science — PickAClass
3.5 (2) ⏱ 3h 📚 30 lessons 🎧 Audio version

R Programming Basics for Data Science

Learn the fundamentals of R programming to import, clean, analyze, and visualize data using modern tidyverse tools.

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  • 🌐 In English
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About this course

Data science starts with the ability to turn raw information into clear, actionable insights. R is one of the most powerful and widely used programming languages designed specifically for statistical analysis and data visualization. In this text-based course, you will build a solid foundation in R programming from the ground up. You will learn how to write clean code, manipulate complex datasets, and generate meaningful visualizations, preparing you to tackle real-world data challenges with confidence. What you'll learn: - Understand essential R syntax, data types, and foundational programming concepts - Import and wrangle datasets using modern tidyverse packages like dplyr - Create clear, professional data visualizations with ggplot2 - Clean and prepare messy, real-world data for analysis - Apply basic statistical methods to summarize and interpret your findings - Organize your workflow using modern R projects for reproducible analysis You will start by mastering basic R syntax and data structures before progressing to data manipulation, visualization, and practical analysis workflows through written explanations and guided code examples. This course is designed entirely for beginners with no prior programming or data science experience required. Start your journey into data science and unlock the power of R today.

What you'll get

  • 📜 Certificate of completion
    Add it to your LinkedIn profile
  • 💬 Personal AI tutor
    Stuck on a lesson? Ask your built-in tutor anything, any time.
  • 🎧 Audio version included
    Learn on the go — no screen needed
  • ♾️ Lifetime access
    Come back anytime, no expiry
  • 📱 Phone or computer
    Works anywhere, any device
  • 💸 14-day refund
    No questions asked
  • Short & focused
    3h of practical content

Certificate of completion

Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.

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Certificate of Mastery
This certifies that
Name Surname
has successfully demonstrated mastery of
R Programming Basics for Data Science
Skills demonstrated
Behavioral pattern analysis
Foundational
1.2 hrs
Decision-architecture frameworks
Proficient
1.4 hrs
A/B test design
Proficient
1.7 hrs
Behavioral copywriting
Advanced
1.9 hrs
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PickAClass — Name Surname
R Programming Basics for Data Science
Page 2 of 2
Performance detail
Coursework summary
Lessons completed 14 / 14
Practice questions 26 / 28
Assignments submitted 4 (avg 4.5 / 5)
Capstone project Reviewed — 4.6 / 5
Total practice 6.2 hrs
Performance benchmark
Cohort rank Top 12% of 1,625
Time to completion 11 days (median: 22)
Mastery score 91 / 100
Practice-question score 94%
Skill verification Verified Skill Path
Verify this credential
pickaclass.com/certificates/PCC-2026-X4F7-AP19
Issued under the academic standards of PickAClass. Skill levels reflect assessed performance against the course's competency rubric. This is an original credential of this platform.

Reviews (2)

Paul Durand FR
★ 4 · July 24, 2026

Good introduction. I appreciated the clear steps, although some of the later modules could have used more examples.

ريم السليمان JO Verified learner
★ 3 · June 1, 2026

It's a good course if you have some prior knowledge. For absolute beginners, some concepts might be a bit challenging. The structure is logical, though.

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What do I need to take this course? +

Just a phone or computer with internet. No installs, no special hardware.

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By card via Stripe. We don’t store card details — Stripe handles them securely.

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Yes — full refund within 14 days, no questions asked.

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Forever. Once you purchase, the course is yours to revisit anytime.

Will I get a certificate? +

Yes. On completion you'll receive a certificate you can add to your LinkedIn profile.

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