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

4.6
étoiles
27,414 évaluations
5,750 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

SF

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.

LR

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.

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3826 - 3850 sur 5,631 Avis pour Les outils du scientifique des données

par Natalia S

Sep 07, 2017

Videos are already sort of "old". Having Macbook i had significant problems with pushing files to GitHub repo, nevertheless I was doing everything said in the videos.

I could do that after using some other functions that were not mentioned in the video.

par Leonardo A

Apr 22, 2019

It was straight forward. However, there were some difficulties installing RStudio using the latest version. I had to go the previous one .e.g. Latest was 3.5 I used 3.4 matching RTools. Other than that very straight fwd, including Github (basic) usage

par Scott D

May 07, 2020

A good course with clear instruction that gives you a basic review of using data and installing R and related programs. Occasionally necessary steps in R are omitted and one has to do some googling. Not a fatal flaw, but frustrating for a beginner.

par Roberto R

Jul 23, 2020

It felt a bit like a RPG tutorial where your big accomplishment is learning how to run or crouch, but I guess it makes sense for it to be part of the Specialization track. I would recommend it as part of a series, more than as a standalone course.

par Carolyn A

Feb 08, 2016

Great introduction to the different tools that a data scientist will encounter and use, including RStudio, Git, and GitHub. I would have appreciated more practical experience linking Git and GitHub, as that is critical for version control of code.

par Samuel M A

Apr 05, 2020

I had some issues in following all the steps that are shown in the lessons. I think the demos skip important steps. But, on the other hand, it forces to search and look for solutions to these issues on the web. Overall: good introductory course!

par Jeroen v B

Sep 12, 2016

It's a good course, you're not going in-depth but this is just an introductory course for the Data Science master and the tools you will use. You will learn the basics of Git and get acquainted with R and is thus somewhat essential for starters.

par Wendell B

Mar 19, 2020

Reviews or Test should rely more heavily on the instruction that goes into detail on a topic matter and questions that were asked on quizes. For example, the datasharing question was worth 2 points, when that topic was only cover very briefly.

par Reinier B

Feb 05, 2018

Although I found the course material in general clear and well-explained, I found the lecture on 'Basic Git Commands' poorly explained and sometimes poorly audible as well. For a non-native speaker of the English language it was hard to follow.

par Shashank S

Oct 30, 2016

This is a good course for someone who is not familiar with the basics of Git,Github and needs to install R,Rstudio and related packages. If you are not the kind of person described above you will be able to breeze through the course very fast.

par Azin S

Nov 22, 2017

The course is very fluent and attractive. You may run into some questions while following the course which you can easily find the answer to by googling it. As a beginner in both Data Science and programming, I'm very happy with this course.

par Sarwar A

Jan 20, 2020

The lectures were good.After all it's robot orienting converstaion it has lot of pace in speech I think that is not good for me.Because It was little bit hard to grasp the message.The pace is only the concerned.Overall lectures were good.

par Kevin J Y

Sep 10, 2017

There are some typographical errors in the quizzes and the english subtitles. Not really a big deal. The Week 2 about GitBash made me a little confused because the video about loading git bash happened before the video about installing it.

par tierny a c

Jul 23, 2018

I don't feel as though the 16 minute video on command lines was efficient. I spent a gross amount of time (over 3 hours) on youtube for supplemental instruction just to complete the final project. Otherwise, this course was sufficient.

par Victor A T

Jan 26, 2020

A very good course for beginner to start off with. This course really helps setup the fundamental toolkit to create a efficient workflow. The git/github version control linking with R/Rstudio is the best thing I got from this caourse.

par morgana

May 24, 2017

Excelent course. The schedule was basic however have approached a thematic complex and important.

The time to complete the tasks week was great.

But I felt need to learn more about git and github. I don't know if it was on follow weeks.

par Marc E S

Feb 25, 2016

Easy to follow. Might be too easy for some people with experience in data analysis. However, the instructors also talk about some frameworks and insights from their experience which could be helpful for even those who have experience.

par Guillermo D H

Oct 17, 2016

El método que sigue el curso me ha sorprendido para bien. Hay determinadas herramientas que aún no comprendo bien qué utilidad podría tener para mí. Quizá porque este primer mes sea muy general. Veremos qué aprendemos este nuevo mes.

par Nil G

Feb 14, 2016

Very good composed, explains in a very good manner the complex topic, a general overview about the tools and their connection to each other would be great and helping, as there are many tools to install and understand the functions.

par Joshua M

Mar 19, 2018

A very good course to learn the different applications needed to start data science. Lectures and examples are easy to understand. Highly recommended to those who would like to know and start a career in the data science field.

par Gágik A

Jul 31, 2016

The course itself only introduces the main aspects and helps with installation of the tools, while no actual programming is taught. But it is useful for having better understanding of the following courses in the specialization.

par Aoife M

Nov 07, 2019

Informative course which provides new information in chunks to make it accessible for all. Varied resources to aid all types of learners and regular assessments are helpful in understanding the learning objectives of each week.

par Katie S

Feb 17, 2017

Super friendly to new beginners with clear definitions and easy-following learning path. Although a bit of slow for me. I'd recommend anyone without programming background to launch their study in data science with this course.

par Andrey S

Jul 06, 2018

A nicely designed introductory course of the specialization. Doesn't' have any sufficient value as a standalone course, still, has crucial importance for the thorough and successful study of other courses in the specialization

par Antonio G M

Jan 03, 2019

It is a nice course. From my point of view it would be great if it included more advanced content but I understand that it is an introductory course so it is ok. In that sense it is great for people that is new to this topic.