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Avis et commentaires pour d'étudiants pour Les outils du scientifique des données par Université Johns-Hopkins

4.6
étoiles
32,448 évaluations
6,924 avis

À propos du cours

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio....
Points forts
Foundational tools
(243 avis)
Introductory course
(1056 avis)

Meilleurs avis

LR
7 sept. 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.

SF
14 avr. 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.

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101 - 125 sur 6,811 Avis pour Les outils du scientifique des données

par Martins P

6 août 2021

Very helpful and well organised, easy to follow and I believe it sets you up very well for the following courses.

If you are looking to learn R and have some previous statistical analysis background (I have learned Minitab 19 for about 3 years now) but have no coding knowledge, I would reccomend not skipping this course as it will help you set up R and introduce you to its basic functions, otherwise it could seem a bit overwhelming.

God bless

par Jesson P

26 juil. 2018

I think that the course is effectively introduces students to the basic toolkit of data science--informative materials, good explanations, and the accessibility to knowledge sharing through the discussion forums.

One suggestion please: It would be very convenient if you could put the links in all the videos in a place where the students could readily access them (contrary to needing to donwload the slide first to be able to access the links).

par Josh C

28 janv. 2016

Excellent. I had a little trouble interpreting my lessons and completing the final project but I figured it out. I was under the impression from the previous videos and the assignment descriptions that I needed to do everything via "Git Bash" in my Mac Terminal, rather than just going and doing it all on Github.com. Either I completely misinterpreted or something was lost in translation right there towards the end. Loved the course though.

par Patricia B

9 nov. 2016

This course is awesome. It takes you by your hand from the very beginning and leads you through all the process to install softwares and sign in on the most up-do-date tools to work on Data Science. And, besides being very friendly, it doesn't stay superficial on the subject. Another highlight is the quality of the material and of the experienced instructors. Excellent value for the investment. Highly recommended if you are a beginner.

par Juha R

11 avr. 2018

I think they have pretty much nailed it with this course/specialization. I have tried several courses on data science from Microsoft, EDX and Coursera and they always seems to lack something. They are either too nimble, lacking the big picture, or they are too long or badly designed. The team is great, they have a very hands on experience on data science and the learning goals are presented in a palatable manner. Excellent course!

par Meghan Z

14 juin 2017

This course provided an excellent introduction to Data Science, the tools used for analysis and basic concepts. It helped me to develop a solid foundation for future coursework in the Data Science track. The presentations are concise, giving necessary details for understanding without excess volume. Plenty of quality references are provided for those, including myself, who want to learn more about the data science discipline.

par Jay D

27 juil. 2018

It was a great start of the specialization course. I completed in just one day. So in fact if you get a time of 4-5 hours in any holiday or free day just do this. It will create interest in you to learn more and more with quick space. I highly recommend this course to the people who has some interest in data science and want to learn more but doesn't get a clue where to start. This is actually a perfect platform to start .

par Catherine I

28 juin 2019

Very good course to get the basics of what the overall specialisation will entail. Great information on setting up your system for any of the other courses in the specialisation. Information on Command Line programming and version control with Git and GitHub set-up proving to be useful. Good to get an introduction to the process of submitting peer reviewed assignments for future courses. Overall good introductory course.

par 黄雅妮

15 oct. 2019

This course is perfectly suitable for people who have passion in R or data science, and has some basic concept of statistics but not a specialist yet. I am a undergraduate student majoring in public health .I choose R for my first scientific tool because of its various utility and applicability to data analysis. But I also want to try to learn some Python in the future. Thank you professors, and my dreamy school--JHU!!

par Dhiraj K

5 nov. 2016

To start with, I have enjoyed this experience of online learning a lot and this is my first online course. The structure of the course is very well designed. The platform is very user-friendly. Although it was just a basic introductory course, it is just a step towards learning more interesting things from a renowned university and very good professors. Looking forward for more quality courses. One step at a time!

par Jade K

23 juin 2020

Comprehensive set up guide and good staging for how to truly be effective in using data to answer questions. Only feedback would be that links should be made clickable from video page and perhaps that notes should be made downloadable. I'd also suggest that when a question is answered incorrectly, recommending users reread notes instead of rewatching the videos as it's easier to skim notes than it is a video.

par Angel G

12 juil. 2020

I enjoyed the lessons. I appreciated the lessons being available in both video and text. While watching the videos I would follow along with the text and if the topics were very technical or heavy with new information I would read the text lesson a second time to help the information sink in. Additionally having the support from the lessons and forums while building my data science toolbox was very helpful.

par Gabriel V d O

9 mai 2020

The teaching methodology of presentation were excellent, I was a little disappointed for not having any more applied exercises. But I believe that my expectations were high and it was necessary to focus only on the tools on this stage. I imagine that this must be the content of the next modules, which I am looking forward to doing. I thank Coursera and JHU for the opportunity granted by the scholarship.

par Lourdes S V

26 déc. 2019

It is a great course for begginers in Data Science. The videos are clear and easy to understand for non-english native people. I think it is overwhelming the first step with the tools: R, RStudio, Git and Git Hub, but, if you dedicate enough time to read the material and manuals, you can do it. The fourth unit was delightful. I learn a lot and I want to say thank Coursera and JHU for this opportunity.

par Ron L

10 août 2018

I have had a Github account for about a year now and I have never used it. Version control is an important part of programming and data science process so being forced to use it by via assignments was a great touch. I am comfortable loading repos now and I have the tools to use Git to have it on my local machine. A great introduction to what is turning out to be a pretty exciting and beneficial class!

par Yi-Wen C

25 sept. 2019

It is a great intro for a beginner if you want to get to know Data science in a broader way. I highly recommend people who are interested in data to join the course. Besides, the course doesn't have to spend many time every week. The content of the course is organized well in a slow path and can also gain more confidence after taking the course, which may be helpful for the following learning.

par Clare G

17 févr. 2017

Very well received by this beginner. I appreciated the time taken to offer an introduction to the command line, which was focussed on the immediate commands needed to continue with this course. Many other data science courses either overlook any kind of command line tuition, or they point you to an overwhelmingly large other tutorial on the subject which would take you 3 weeks to complete.

par Charles D

5 juil. 2016

This is a nice course on getting and installing the data scientist's tool box. In the future, this course should be improved with an example of creating files in Git and pushing them to GitHub. Although issues were addressed by peers in the class, going through an example before the course project will very much help future students with no experience. Great course. I highly recommend it!

par Christopher A C

28 mars 2016

This is a wonderful introductory course. I allows one to get an idea if they would like to continue towards the specialization. I would suggest taking this course with the R-Programming course. I have a very basic knowledge of Data Analytics and I could have taken the first two course simultaneously. However if you have a incredibly busy schedule just taking this course would be fine.

par David S

17 nov. 2021

The course is straightforward and easy to follow. Basically its a brief (but broad) introduction to what Data Science is & its applications. Most important skill that I learned from this course is how to set-up a version control for your R scripts. I have no idea it can be integrated to a version control before I took this course (coming from a different career background - mech engg')

par Brooks A

1 oct. 2020

This is a great course to help you set up the tools required to start a data science project. The pacing is perfect. Each lesson conveys just the right amount of information without being overly explanatory. I had some issues receiving feedback on my end-of-course project. However, this is not the fault of the instructors or course content. Rather, it is a flaw in the Coursera model.

par Francis P

29 oct. 2019

I recommend that beginners, coders new to data analysis and anyone seeking foundational experience with Git, collaborative coding or the R programming language start here. It does not dive deep, but does introduce interfaces, basic syntax, routine operations and some commands in the technical setup portion, and also goes into test design and glosses the general field of study nicely.

par Justin A

15 juil. 2019

Excelente curso. Brinda una introducción a la ciencia de datos (Data Science) y las capacidades de este campo. Se configura RStudio y se aprende a utilizarlo, junto con los repositorios de GitHub, y se muestra la manera correcta de obtener ayuda con los problemas que puedan presentarse. Al final, se crean archivos con RMarkdown, y se introduce Big Data y el pensamiento estadístico.

par Sheri M W

7 juin 2016

This class is a great introduction to the tools needed to begin working on data analysis. The assignments provide just enough instruction to cover the basics and propel you toward uncovering additional information on your own. The assignments are structured in such a way that you must pay close attention to the lectures; then analyze and apply them on your own. Great course overall.

par Rachael M

25 juil. 2020

Learned SO MUCH! I can't believe how much I actually learned. The course is set up so you are forced to download and practice using RStudio and Githun (both free), and are guided through it. Not too hard, not too easy either. Just challenging enough. Also appreciate that I didn't have to spend 10k on a bootcamp when I wasn't even sure that I liked data analysis. Now I know I do!