COMIDOC
CouponsFreeTopics
COMIDOC
CouponsVerified CouponsFreeFree CoursesTopicsTopics
React
AdvertiseSubmit Course

About

Udemy coupons monitored continuously

Verified offers, course alerts, precise filters, and browser detection built for learners who want coupons that still work.

TelegramTwitterFacebookRSS

Browser tools

Find coupons directly on Udemy

The extension surfaces an available Comidoc coupon while you browse a Udemy course page.

ChromeFirefoxEdgeSafari

Useful links

Discover

  • Blog
  • Daily Freebies
  • Most Wanted Coupons
  • Coupon Statistics
  • Top Contributors
  • Udemy Sale Calendar

Services

  • Pricing
  • Advertise Here
  • Guest Post
  • Developer API
  • Submit Coupon

Comidoc

  • About
  • Contact
  • Data License
  • Privacy
  • Service status
  • Terms

© 2017–2026 Comidoc

v6.8.65

Independent coupon discovery for Udemy learners

R Programming for Statistics and Data Science

R Programming for Data Science & Data Analysis. Applying R for Statistics and Data Visualization with GGplot2 in R

  1. Topics
  2. Development
  3. R Programming & Statistics

R Programming for Statistics and Data Science

Instructor365 Careers
Duration6h 42m
Students32.8K
Rating4.6 (5,898)
Sponsored
Price
$17.99
Coupon
None
No active coupon currently available
Access
Email alert
We will email you when a verified deal appears
Open on UdemyCurrent Udemy price
Comidoc Analysis

R Programming Fundamentals and Statistical Analysis

Editorial course preview

What the public course preview actually shows

These 3 complementary views highlight concrete, legible examples from the course presentation.

Preview 1 of 3

The presenter discusses data manipulation techniques in R, with text overlays highlighting specific functions such as index, subset, and spread alongside key course topics.

Preview 2 of 3

The presenter is shown alongside five key course highlights: fantastic learning pace, programming fundamentals, data manipulation techniques, step-by-step statistics introduction, and balanced theory with practice.

Preview 3 of 3

The presenter is shown sitting on a sofa with a text overlay stating '125,000+ students', highlighting the course's popularity.

Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.

More R Programming & Statistics courses

Machine Learning A-Z [2026]: ML, DL, AI with AWS, Python & RKirill Eremenko4.5 (206.8K)49h 15m
Machine Learning & Deep Learning in Python & RStart-Tech Academy4.4 (6,025)33h 12m
Complete Machine Learning with R Studio - ML for 2025Start-Tech Academy4.5 (2,606)12h 1m
Artificial Neural Networks (ANN) with Keras in Python and RStart-Tech Academy4.5 (1,021)8h 37m
R Programming For Absolute BeginnersBogdan Anastasiei4.5 (3,219)9h 33m
Free
Data Science, Machine Learning, Data Analysis, Python & RDATAhill Solutions Srinivas Reddy4.2 (2,993)8h 7m
Data Science: R Programming Complete DiplomaSDE Arts4.3 (1,250)5h 7m
Logistic Regression in R StudioStart-Tech Academy4.2 (406)6h 17m

Strengths

Integrated Practice Cadence

The curriculum utilizes a frequent pattern of video lectures followed by specific article-based exercises to reinforce concepts.

Comprehensive Statistical Scope

Instruction covers descriptive statistics, hypothesis testing, linear regression, and data visualization via ggplot2.

Limitations

Technical and Statistical Aging

Learner signals suggest some code snippets may be outdated for modern R versions, alongside potential inaccuracies in the interpretation of null hypothesis testing.

Best suited to

  • Beginners seeking an introduction to R
  • Learners interested in statistical theory application

Less suited to

  • Those requiring up-to-date modern R (v4+) syntax
  • Advanced programmers looking for deep technical depth

Comidoc Score

7.6/10

Recommended
Beginner-friendly

Comidoc verdict

The learning path begins with RStudio setup before progressing through programming fundamentals, Tidyverse manipulation, and statistical analysis. The curriculum is structured around a frequent cycle of video lessons and practical exercises designed to build confidence in data handling.

Instructional clarity is often noted as high for beginners, yet technical debt remains a factor. Some learners have identified code that does not align with modern R defaults and potential errors in statistical theory application. Additionally, inconsistencies between spoken and written content may arise.

This course is best suited for absolute beginners who want a structured introduction to R and statistics, provided they are willing to cross-reference code with current documentation.

Score breakdown

Curriculum depth
8.8

The curriculum covers a wide range of topics from basic programming to regression and visualization.

Applied learning
9.5

The course includes a high volume of hands-on exercises to reinforce learning.

Clarity & experience
6.5

Instructional signals are mixed; while many find it clear, others note inconsistencies and pacing issues.

Currency & reliability
3.5

Learner feedback indicates that some code and statistical interpretations may not align with modern R standards.

Audience fit
8.0

Instructional Inconsistencies

There are reports of discrepancies between oral and written instructions, as well as typographical errors in presentation slides.

The curriculum aligns well with the stated goal of teaching beginners R and statistics.

More Related Topics

  • Data Science Fundamentals1063
  • Statistics Mastery371
  • Data Visualization & Dashboar…1464
  • ggplot2 Visualization33
  • Statistical Modeling110
  • Machine Learning (ML)2167
  • Statistical Computing34
  • Multivariate Analysis15
  • R Markdown12
  • Text Mining Techniques41