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Linear Regression and Logistic Regression using R Studio

Linear Regression and Logistic Regression for beginners. Understand the difference between Regression & Classification

  1. Topics
  2. Development
  3. RStudio Workflow Mastery

Linear Regression and Logistic Regression using R Studio

InstructorStart-Tech Academy
Duration6h 16m
Students62.3K
Rating4.7 (372)

Coupon history

Comidoc has tracked 1 coupon for this course since 2025, last checked 1 year, 20 days ago.

Coupon codeDiscountAddedStatusLifetime
SMARTLEARNFREE100% offSep 30, 202508:21 PM UTCExpired~4 daysRan full term
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Price
$12.99
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Comidoc Analysis

Statistical foundations and R syntax alongside regression modeling

Strengths

Statistical and R Fundamentals

The curriculum establishes a base through measures of center, dispersion, and introductory R syntax.

Practical Application Elements

Instruction includes hands-on exercises and professional role-play simulations for interview preparation.

Editorial course preview

What the public course preview actually shows

These 2 complementary views highlight concrete, legible examples from the course presentation.

Preview 1 of 2

A promotional graphic featuring two R logos, a superhero silhouette, and a scatter plot with a red regression curve, accompanied by presenter headshots and the Start-Tech Academy name.

Preview 2 of 2

A vector illustration of a business presentation showing a presenter, audience, and a list of R course topics.

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

Limitations

Technical Debt and Tooling Obsolescence

Some utilized packages may no longer function with current R versions, and the workflow lacks modern tidyverse integration. Note that a 2022 review signal predates the displayed update date; therefore, the update label does not prove these issues were corrected.

Instructional Discrepancies

Some utilized packages may no longer function with current R versions, and the workflow lacks modern tidyverse integration. Note that a 2022 review signal predates the displayed update date; therefore, the update label does not prove these issues were corrected.

Best suited to

  • Beginners seeking a statistical refresher
  • Learners wanting to understand R Studio setup
  • Individuals preparing for data science interviews

Less suited to

  • Those seeking modern tidyverse-based workflows
  • Advanced practitioners requiring high code reliability

Comidoc Score

6.4/10

Worth considering
Beginner-friendly

Comidoc verdict

The learning path covers essential statistical concepts, such as data types and measures of dispersion, before moving into R Studio environment setup and data preprocessing workflows. This foundation is followed by the implementation of simple/multiple linear regression and logistic regression modeling.

Technical limitations present a notable risk; specific signals indicate that certain packages used in the curriculum may be outdated for current R versions, and there are reports of discrepancies between provided code and instructor demonstrations. Furthermore, the instruction relies on older methods rather than modern tidyverse-based data science workflows.

This course is best suited for beginners who need a broad introduction to statistics and regression logic, provided they are prepared to troubleshoot environment or package issues independently.

Score breakdown

Curriculum depth
7.3

The curriculum covers a wide range of topics from basic statistics to specific preprocessing steps and regression models.

Applied learning
7.3

The course includes practical exercises and interview simulations to reinforce learning.

Clarity & experience
4.3

One signal predates the displayed update; the update may have addressed it, but the update label does not prove that it was corrected.

Currency & reliability
5.8

This signal predates the displayed update; the update may have addressed it, but the update label does not prove that it was corrected.

Audience fit
6.5

The curriculum aligns well with the stated beginner goals and statistical foundations.

More Related Topics

  • Linear Regression63
  • Generalized Linear Models6
  • Statistical Modeling97
  • R Language for Data163
  • Data Analysis & Reporting2126
  • RStudio Environment38
  • Tidyverse Ecosystem19
  • R Programming & Statistics303
  • Software Development Tools117
  • Development Workflow16