Data science with R: tidyverse (Udemy.com)

Formation dispensée en anglais par un professeur patient, dont la maîtrise du sujet a été irréprochable du début à la fin. Le contenu est d’une qualité remarquable pour toute personne souhaitant apprendre R, en particulier les Tidyverse, dplyr et l’utilisation des pipes. Cette formation m’a également permis de progresser sur des aspects essentiels : - la construction et l’utilisation des fonctions en R, - la réalisation de graphes avec ggplot2, -l’analyse de données avec R. Le projet Covid‑19, exigeant et structuré, couvre les notions de R depuis les bases jusqu’aux concepts avancés, ce qui en fait un excellent fil conducteur pédagogique. Je recommande vivement cette formation : le temps et l’énergie investis sont largement récompensés. Elie YODI 26 Juillet 2026

presentation is chaotic, as if there's no preparation or script, making it annoying to follow.

amazing course with great material and great explaintion, but if you can change the final project as it has a lot of missing data and i am sure you can do much much better with your skills sir, Thank you

The instructor is clearly knowledgeable and has a passion/eagerness for exploring and guiding. This course covers a lot of material. At the same time it lacks demonstration of practical applications. The style of teaching resembles that of a teacher trying to cover as much of the syllabus as possible. Only the final project is near to any practical application. However, the instructor just rushes across the project without adequately explaining the "whys" and "hows". And the instructor has tried the "code along" approach which is good, but a lot of bugs appear in the programs which is distracting and debugging takes a lots of time. I have learnt a lot of theories in this course. But I am not sure about applying the same in any real world scenario.

This is an awesome course to get familiar with R and R studio and explained with every bit of detail. Great mixture of Theory and Practical classes. I just don't understand why there are not many students compared to other courses. Great job, and I've even bought a Data Visualization course in R.

Instructor did a lot of prep work to create this course. The 31 hours of content is intimidating, but each lesson is covered twice - once as theory and once as practical demonstration. Different learners will want the different parts, the slides, the demonstration video, and the actual R file for each section which is downloadable as a resource. Lots of new material is presented in the homework walkthroughs. The lectures don't prepare you entirely for the homework, in the walkthroughs he pulls in new concepts that haven't been covered yet. So the homework walkthroughs are definitely worthwhile.

I've never seen a more structured course even In platforms or in standard education programs in universities. I'm studying a masters degree in Data Science and I have a good level of python programming, however most of my teachers use R in class, so the learning curve had been really steep for me the first semester. I've been following this course for the last two months and I think it will be very helpful in order to have a better performance in my next semester at the university (I'll let you know updating this review).

Wow, what a ride. This course is an amazing primer for R, tidyverse and data wrangling with basic data visualization techniques put into mix. There are also some advanced topics that really opened up a broad new horizon for me to explore (hint: bang!!! - functional programming). Scripts and assignment solutions are also provided so it's easy to follow along. All in all - it's well worth to invest time for a deep dive into data science fundamentals. Two thumbs up!

This is a fantastic course for beginners, I bet! It is more beneficial when one practices side by side with the Instructor with another sample data and see how the same codes become something else in a different context and understand the applications. The instructor has put fantastic effort to convey most things in the course. One great addition to the course can be focussing on different types of common errors that a novice expects to receive when he/she applies it to a different dataset, and why it is important to understand. For example, "Can't coerce element 1 from a character to a double". Overall, I have learned a lot from this course and I recommend it highly.

I find explanations clear, to the point, and fluid. I am truly satisfied with this course. I am not yet where Regex is taught, I feel it is a topic that needs a book for itself. Not even "R for Data Science" tryies to go deep with that one.