Apr 15, 2020
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.
Sep 08, 2017
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.
автор: Donna O•
May 19, 2020
It is a nice course which smoothly familiarize a novice data science learner to the nature and tools of their job. Although I prefer it to be taught by a real instructor instead of a robot, apart from that everything was designed carefully to introduce data science toolbox to people.
автор: Ricardo J d S•
Dec 17, 2018
Achei de grande valia, no meu caso, especificamente, por me colocar novamente em contato com a parte mais técnica da TI - venho desempenhando papéis gerenciais a algum tempo e tinha certo receio de alterar a configuração da minha máquina para ser um "laboratório" de ciência de dados.
автор: Farkhadov Z•
Aug 08, 2016
Good course for begginers like me. All information is provided very simple and it's easy to understand. Also involves srudents not only looking videos but offer books. In addition you will need to search some information yourself to complete some tasks.
Thanks for this great course.
автор: VEERA V•
Dec 08, 2019
Even though it is a starter course to the specialization learned so many new things like amazon polly which is being used to generate these videos, R-markdown and how important is it to produce reproducible research.
A must take course for any data science aspirant
автор: Ting L•
Aug 24, 2018
It's a great course for beginners. I had little knowledge about data science. I didn't even know what was R and GIt. After taking this course, I had a preliminary understanding of them. If anyone wants to learn data science without any experience, this one can be your start point!
автор: Tristan I•
Jan 17, 2020
All the information felt applicable to my current role. The main thing I gained from this course is that I feel more confident in the tools at my disposal as a data analyst. Additionally I learned about tools I had never heard of & how to utilize them, and for that I'm thankful!
автор: Dominic C•
Apr 25, 2016
Great way to learn R and become familiar with how to use it. As a developer with an understanding of Python, Java, C and C++ I could quickly see how to use R, how to extend it and start working with it today. Very good use of supporting tools like Swirl to assist with teaching.
автор: Michael S•
Feb 20, 2018
I found this course to be effective at getting the student to recognize the baseline set of tools, skills and behaviors expected in courses 2-10. Moreover, none of said tools, skills or behaviors fall outside the confines of typical and/or "in demand" experience. Nice work!
автор: Prithvi M•
Mar 11, 2020
Great course to get started with data science using R as primary language. Good data practices are encouraged and use of GitHub for version control gives additional confidence to anyone wishing to preserve their work that leads them up to the solution to the problem at hand.
автор: Francisco M R O•
Aug 27, 2018
It's an excellent introductory course for the specialization, I have recommended this course to a friend because I have found the content pretty useful. I will continue with the other courses of the specialization and I'm very grateful to have this opportunity from Coursera.
автор: Oyetunde A O•
Aug 13, 2017
This is a nice course and well taught by all facilities made available by the facilitators. As soon as am financially able to start to finish from where I stopped, I will activate my remaining course left to roundup Data Science Specialization.
I really appreciate. Thank you.
автор: Peres R B•
Apr 03, 2016
Basic course introducing the minimum tools to start your journey in data science. The course was very important for me to get up to speed with Git and GitHub. All the information was given in a concise and objective way, yet covered all basic important points of such tools.
автор: Suryadeep D•
Mar 17, 2016
Might look trivial at first glance to more experienced users, but was very much essential for a complete beginner like me. Gives a nice overview of a somewhat overwhelming (and sometimes intimidating) field and equips you with the basic tools necessary (like how to use git).
автор: AKHIL K•
Apr 11, 2020
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).
автор: Arthur D•
Apr 11, 2016
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).
автор: Anatoli K•
Mar 14, 2019
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.
автор: Hrishikesh P H•
Apr 16, 2020
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.
автор: BHAGAWAT M•
Jan 29, 2020
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.
автор: Juan C J T•
Jun 12, 2018
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.
автор: Daisuke I•
Mar 07, 2016
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.
автор: Ahmed M K•
Oct 01, 2016
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.
автор: Joan S D C H•
Sep 06, 2019
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.
автор: Richard E H•
Apr 27, 2018
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.
автор: Kevin C B C•
Nov 06, 2017
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.
автор: Roberto A•
Mar 11, 2017
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!