R Programming for Data Science & Data Analysis. Applying R for Statistics and Data Visualization with GGplot2 in R
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The curriculum utilizes a frequent pattern of video lectures followed by specific article-based exercises to reinforce concepts.
Instruction covers descriptive statistics, hypothesis testing, linear regression, and data visualization via ggplot2.
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
The presenter discusses data manipulation techniques in R, with text overlays highlighting specific functions such as index, subset, and spread alongside key course topics.
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.
The presenter is shown sitting on a sofa with a text overlay stating '125,000+ students', highlighting the course's popularity.
Learner signals suggest some code snippets may be outdated for modern R versions, alongside potential inaccuracies in the interpretation of null hypothesis testing.
There are reports of discrepancies between oral and written instructions, as well as typographical errors in presentation slides.
Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.
The curriculum aligns well with the stated goal of teaching beginners R and statistics.