As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.
It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.
by AKHIL K•
The "Data Scientist's Toolbox" offered by Johns Hopkins University is a good head start for the newbies in the field of Data Science. The course gives the brief introduction to various software used by a Data Scientist that is R, R studio, Git hub and Git (version control).
by Nthabiseng M•
I really enjoyed the course, the quizzes are very helpful because they taught me to listen and watch the videos carefully so that I can remember the content. As an IT student this course will be very helpful to me, and will open more opportunities for me in the ICT sector.
by Arthur D•
Very good introduction to data science. It gives a general overview on data and its problematics but also tips and help on how to start with the basic tools that will be needed (I haven't done any R programming and didn't have a github account so that was helpful for me).
by Bhavay S•
It is a very good course to get introduced to the world of data science. Working knowledge of R, RStudio and GitHub is covered in a very nice and organised manner. I feel more confident and equipped to proceed further and learn how to solve problems through data science.
by Анатолий К•
Интересно было посмотреть как работает один из лучших исследовательских университетов мира.
Кроме настройки программного обеспечения много узнал об основных принципах науки о данных.
Очень понравился пример с Хилари Клинтон. Возможно это был роковой момент в её поражении.
by Samuel W•
This is not a coding course. It is a course to bring you up to date with the logistics of using R: downloading packages, using RStudio, using GitHub version control, and familiarizing oneself with the overarching concepts of experimental design, statistics and big data.
by Hrishikesh P H•
A very easy to understand, nice and simple course. ample quizzes and puzzles available. A recommendation : please include a thing or two about RStudio Cloud. Especially, please include how to tie up your github repo to RStudio Cloud; as the procedure s different for it.
by BHAGAWAT M•
It's really enjoyable, a lot to know and a lot to discuss. The other links provided for more details are very much helpful. The feature of the discussion form is very helpful. Thanks, to Coursera and the team of Coursera for your high great work to open this platform.
by Juan C J T•
Muy buen curso introductorio en el que se pueden observar las herramientas necesarias para realizar análisis de datos, además de que muestran quienes son Científicos de Datos en la actualidad y qué tipo de análisis realizan, todo adquiriendo la información de internet.
by Daisuke I•
Setting up the environment is often the tricky part that deters people from moving into, or back into coding. This class provided me with a hand-holding needed to start coding again. I recommend this course as a kick starter for those who were on legacy environments.
by Kimiora H•
The course content is great, with great real world examples linked to the topics.
The quiz questions are of varying difficulty, most are easy if you give the right time to the course, but some can trip you up if you don't put the necessary thought and time into them.
by Ahmed M S K•
What a great introduction. It needs a lot of reading and self developing to be able to do that project at the end. It's kind of difficult but you'll feel that you've really learned something that will be useful for the rest of your life. Thanks JH and Coursera staff.
by Joan c h•
Es un buen curso. te lleva de la mano pero no te da todo digerido en cierto momento debes buscar alguna solución para las tareas que te piden pues por razones de versiones ya no funciona igual.
Sin embargo el contenido temático es lo importante y me pareció perfecto.
by Richard E H•
A good introduction to analytical processes and tools. The course by itself, however, is only a first step. I find many threads begun but not tied together. I anticipate that the remaining nine courses will expand and consolidate everything opened in this course.
by Pedro A•
Es un excelente curso, te insta a ser ordenado en tu trabajo con el uso de las herramientas que existente para que podamos a cada proyecto que tengas y podamos refrescar rápidamente todo el historial con el control de cambios. ¡Excelente introducción del Programa!
by Mark K•
The course is great at explaining the preliminary steps for setting up an R development environment and describing the basics of data science. Videos were paced well, not being too short or long, which allows the viewer to stay focused and interested. Recommended.
by bekir y a•
Quite helpful course in teaching the fundamentals of data science, do not expect to use statistical analyses programs effectively with the help of this course. This course's main aim is on teaching the fundamentals of data science just like we see in a university
Super!, I was an excellent way to start the certification, and also a very good motivation to learn about contents included ( R, R markdown, github, control advance) . At the final of all, it is not possible to run if we do not to learn to walk. Thanks for it .
by Rajat A•
Very well paced course with a well structured approach to the toolkit. I would encourage people to take this course to get a hang of the basic working environment. It works even better if you already have a strong foundation in Statistics, and Research Methods.
by Kevin C B C•
A very eyeopening introduction to the discipline of Data Science. Hope this prepares me for R programming soon. :) I also realized how relevant this is today especially in the sciences, wherein one must have a good grasp in programming as an aid for research.
by Roberto A•
I found this intro course really useful as a warm up and to get into the "data scientist's mindset". The only (minor) point for development is to devote more time to Git and Github, as some of the steps were not particularly straightforward. Well done though!
by Eduardo A•
I really loved the course. My peers were amazing. They always help and when they review your project they make sure that you will understand what you did wrong, explaining why and how you might gei it right the next time. Mr. Peng you are amazing. Thank you!
by Sandra N•
This is a fantastic way for individuals to get a leg up if they want a competitive edge in an ever-changing scientific environment. It is important to be able to use certain programs and code to some degree in order to be competitive using today's technology.
by Drew P W•
The course was well put together and documented. My only critic is that I would like the lecturer to go over Git and Github more thoroughly as I had to do some extensive outsourcing to be able to figure out how everything worked. Overall, a very good course.
by Saurabh C•
Best in it's Class. Short but so much descriptive with a constant effort to deliver high quality teaching with easy understanding language and concepts!
It's highly recommended to those who are new to Data Science, and want to make their Base strong( like me)