12 avis pour R Programming A-Z: R For Data Science (Course & Exercises)
Note 5 sur 5
Metilda Sitali Ntomwa –
I used R for the first time in a Time Series course of the Masters in Applied Econ and I was lost most of the time. After graduating my masters programme, I wanted to sharpen my R skills. R-Programming A-Z truly is a good course that helped me understand so many things about R that I did not understand before. I am definitely more confident with my R skills now. As a central bank economist, working particularly in Balance of Payments section, I look forward to putting to use in my job my newly acquire R skills.
I deal a lot with multiple variable stacked bar charts, beside the histograms, density charts, correlation and boxplots, it would have been great if the different types of charts were covered too. But, with my new R skills, I should be able to relatively figure this out.
Thank you Kirill!
Note 4 sur 5
Chinenye Miracle Ebisi –
Awesome experience. Information is broken down bits by bits such that one who has no prior knowledge of R flows with concept and teachings
Note 5 sur 5
Monalisa Mishra –
Voila! Glad that I found the best course and I must say Kirill is an awesome instructor. The flow of the topics in this course is well illustrated and I am all charged up to deep dive into the subject. Happy learner.
Note 5 sur 5
Tiana Le –
This is a great introductory course to learn R. Learning objectives include reviewing data elements and packages to applications with real datasets. Thank you for summarizing R so well and creating great homework assignments.
Note 4 sur 5
Yushail Naidoo –
Amazing course! This course was easy to follow and it was great to get practical examples to apply the skills learnt throughout this course. It has helped me solidify my R basics and taught me how to create amazing visualizations that can be used to analyze data sets. I would highly recommend to any beginner looking to learn R programming.
Note 5 sur 5
Fanny Lööf –
I took this course to prepare for a master’s in Educational analysis. My background was a degree in early childhood education, so I only had experience with qualitative analysis. This course helped me prepare for the initial data science course in my program and I could “hit the ground running”.
Note 4 sur 5
Garry Kelley –
Good course overall. However, the lectures became longer over time and had long intervals of time between lecture and practice sets/homework. Also, some of the problems sets relied on functions that weren’t talked about in the lecture series but were given as hints at the beginning of homework sessions.
Note 5 sur 5
Manuel Vieira Siqueira de Arantes –
Excellent course! I knew absolutely nothing about R programming and this course exceeded my expectations. Kirill has solid knowledge in R and manages to convey this knowledge very precisely
Note 5 sur 5
Chathupa S. Dewasirinarayana –
I finished this course, and I can ensure that this is a great course for a complete beginner in data science.
Note 5 sur 5
Ayako Kimijima –
R was a concise, elegant language than I expected and I might felt that way because this tutor’s cheerful, encouraging attitude towards the course made me eager to learn more. However, students should also be aware that the latter visualization sections have a lot to memorize, and the grammar of visualization tends to be lengthy and tricky. That being said, with the help of “?” and memos taken from the courses, I might be able to explore further in the world of R, all thanks to the tutor.
Note 4 sur 5
Shekhar Thumake –
This course helps you learn R base programming concepts. I have taken several courses from Kirill and they give you good foundation of the topic. I just have one recommendation to further improve this course. If they can add more exercises for the students to practice the concepts then the learning will be even more engaging. Overall, I thoroughly enjoyed this course and learnt a lot. Looking forward to start the ‘Advabce R Programming Course’ from Kirill which I have already enrolled into.
Note 5 sur 5
Linda Breeman –
I learned so much in this course. At the moment, I am eager to try out my new visalization skills on my own challenging data set.
Metilda Sitali Ntomwa –
I used R for the first time in a Time Series course of the Masters in Applied Econ and I was lost most of the time. After graduating my masters programme, I wanted to sharpen my R skills. R-Programming A-Z truly is a good course that helped me understand so many things about R that I did not understand before.
I am definitely more confident with my R skills now. As a central bank economist, working particularly in Balance of Payments section, I look forward to putting to use in my job my newly acquire R skills.
I deal a lot with multiple variable stacked bar charts, beside the histograms, density charts, correlation and boxplots, it would have been great if the different types of charts were covered too. But, with my new R skills, I should be able to relatively figure this out.
Thank you Kirill!
Chinenye Miracle Ebisi –
Awesome experience. Information is broken down bits by bits such that one who has no prior knowledge of R flows with concept and teachings
Monalisa Mishra –
Voila! Glad that I found the best course and I must say Kirill is an awesome instructor. The flow of the topics in this course is well illustrated and I am all charged up to deep dive into the subject. Happy learner.
Tiana Le –
This is a great introductory course to learn R. Learning objectives include reviewing data elements and packages to applications with real datasets. Thank you for summarizing R so well and creating great homework assignments.
Yushail Naidoo –
Amazing course!
This course was easy to follow and it was great to get practical examples to apply the skills learnt throughout this course.
It has helped me solidify my R basics and taught me how to create amazing visualizations that can be used to analyze data sets.
I would highly recommend to any beginner looking to learn R programming.
Fanny Lööf –
I took this course to prepare for a master’s in Educational analysis. My background was a degree in early childhood education, so I only had experience with qualitative analysis. This course helped me prepare for the initial data science course in my program and I could “hit the ground running”.
Garry Kelley –
Good course overall. However, the lectures became longer over time and had long intervals of time between lecture and practice sets/homework. Also, some of the problems sets relied on functions that weren’t talked about in the lecture series but were given as hints at the beginning of homework sessions.
Manuel Vieira Siqueira de Arantes –
Excellent course! I knew absolutely nothing about R programming and this course exceeded my expectations. Kirill has solid knowledge in R and manages to convey this knowledge very precisely
Chathupa S. Dewasirinarayana –
I finished this course, and I can ensure that this is a great course for a complete beginner in data science.
Ayako Kimijima –
R was a concise, elegant language than I expected and I might felt that way because this tutor’s cheerful, encouraging attitude towards the course made me eager to learn more. However, students should also be aware that the latter visualization sections have a lot to memorize, and the grammar of visualization tends to be lengthy and tricky. That being said, with the help of “?” and memos taken from the courses, I might be able to explore further in the world of R, all thanks to the tutor.
Shekhar Thumake –
This course helps you learn R base programming concepts. I have taken several courses from Kirill and they give you good foundation of the topic. I just have one recommendation to further improve this course. If they can add more exercises for the students to practice the concepts then the learning will be even more engaging. Overall, I thoroughly enjoyed this course and learnt a lot. Looking forward to start the ‘Advabce R Programming Course’ from Kirill which I have already enrolled into.
Linda Breeman –
I learned so much in this course. At the moment, I am eager to try out my new visalization skills on my own challenging data set.