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Learner Reviews & Feedback for The Data Scientist’s Toolbox by Johns Hopkins University

4.5
19,109 Bewertungen
3,834 Bewertungen

Über den Kurs

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....
Highlights
Introductory course
(1056 Bewertungen)
Foundational tools
(243 Bewertungen)

Top-Bewertungen

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.

AM

Jul 22, 2017

Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.

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1 - 25 of 3,809 Reviews for The Data Scientist’s Toolbox

von Jitin V

Aug 13, 2018

Good to set you up for advance courses.

von Anthony V

Aug 16, 2018

Great course, really helps get you into the right mindset for becoming a data scientist.

von kaan b

May 28, 2019

Not met what offered. I really don't know why but Instructor was in a hurry and like, he was in the position of instructor by obligation.

Maybe, He has knowledge of the subject, but definitely does not have even basic skills of teaching.

Because of this course, I am not planning to follow other courses on this specialization.

von Frederik C

Aug 13, 2018

Great intro

von Aryan G

Jul 01, 2019

This is a very good course as it tells you some basic and is mostly the introductive course for the entire specialization.

von Khaleel u r

May 22, 2019

execellent i am very to gland get this certificate .. it is so valueable for me. the first one of data science track

von Andrea R C

Apr 11, 2019

A great intro to the course. I am not the biggest fan of the automated voice, but it gets the job done. I do like the secondary lessons written out with bulleted lists and close-ups of the slides. That is like a helpful review.

von Paul R

Mar 13, 2019

Basic introduction for the specialization, principles of data science, and installing stuff, it's fine to get started but could get hands dirty with R more quickly. Overall the plethora of 4-5 star reviews for this specialization seem generous. You will learn a good deal but there is heavy focus on R and academics of data science (Rmarkdown, Knitr, shiny apps etc), only 3 courses (6,7,8) get into meat of statistics/regression models and ML; the capstone project is interesting but doesn't use much of this stuff, it gets bogged down in technical work with new R libraries for text processing. The material is a few years old and not being maintained, discussion forums and interest/participation feels stale. Take some time to look at syllabus and compare to other courses for what you want to learn before committing many months to this specialization.

von sonal g

Feb 03, 2019

Providing feedback means giving students an explanation of what they are doing correctly AND incorrectly. However, the focus of the feedback should be based essentially on what the students is doing right. It is most productive to a student’s learning when they are provided with an explanation and example as to what is accurate and inaccurate about their work.

Use the concept of a “feedback sandwich” to guide your feedback: Compliment, Correct, Compliment.

von SANJEEVE K G

Jan 24, 2019

Coursera has given new life to me

von Aman U

Jan 05, 2019

Good but need more explanations for topics.

von David S

Dec 20, 2018

This course was in many ways the first day of lectures, get your syllabus, buy your books, install your tools, etc. I would give it 5 stars but the lectures inclusion of internet addresses that aren't links and aren't included in the transcript led to a lot of time paused and typing out long addresses.

von Usenaliev N

Dec 08, 2018

Would be great to have more reading materials

von Tolga T

Nov 24, 2018

!!!STOP DON'T TAKE THIS COURSE!!!

%100 pure advertising. There is a moment I felt like I learned some thing, but rest of the course I played with x2.0, of there was more I would have get it.

Putting this into Specialization requirements is smart from your perspective, you are basically saying if you want to reach Capstone pay me $50 more, but at least fix the typos you made during video, just a little respect to your subscribers. But right now, I highly doubt that Capstone Project will be something serious that I want to mention in my Linkedn. There is also downside of what you do. But since you are in between the top rated courses either nobody uses Coursera anymore or people are silent enough and patient enough.

You are all Scientists like me, I'm also biostatistician but I would never ever post a course like this to any platform. I'd rather use Google or Facebook ads to lead people here.

If somebody wise enough to get Data Science Course, he should be skillful enough to download R, click next and install it, and R has help for it, shows you step by step. GitHub is free platform, anyone who can signup for Coursera can signup for GitHub, too.

I know there is no requirements for this course or specialization course, it is 0 to Scientist but seriously you are talking about R codes, arrays, loops, regression, model fit but signing up for GitHub.

Your target group in Coursera is either Data Scientist or becoming one, so they know what the Data Scientist job posts requires.

It requires coding blind folded R/Python/Java/one of C family at least 2 of them, hopefully all of them.

It requires SQL, MySQL, NoSQL, any kind of SQL or database solution mankind ever used.

It requires Math, Statistics, Analytics, Algebra, Finance, Economics + all kinds of computational sciences

It requires management, social relations, advertising, psychology, anthropology + rest of the social sciences.

+++++ it requires LOGIC and NON-ARTIFICIAL HUMAN INTELLIGENCE

so we are trying to be that guy, no need to show installing R or GitHub, I'm sure you will do it again doing rest of the Specialization.

von JEFFERSON D S N

Aug 31, 2018

SIMPLESMENTE SENSACIONAL !

von Jasmine P G

Aug 16, 2018

The course is clear and good to learn,

von Pratyush M

Aug 13, 2018

A bit basic, but a great start for beginners.

von PALAKOLLU S M

Aug 10, 2018

Teaching of lessons are simply amazing.

von William C

Sep 26, 2017

I really don't know much about this stuff, I think the jury's still out on whether the last four weeks will be helpful in the future. We'll see how much I think I've learned at the end of the course

von John S

Jul 15, 2019

Most helpful for those who don't exactly know what they are doing and need help setting up R, R Studio, GitHub, and Git. Be warned, o actual programming here. However, I definitely appreciate what I learned.!

von sebastian p d

Jul 15, 2019

clear guidance

von Justin A

Jul 15, 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.

von Wei D

Jul 14, 2019

Good starting point for beginners to learn about R. Basic experience with git is a must although it is possible for complete beginners. Will just take more time to do the homework and quizzes.

von Udom A

Jul 14, 2019

Very good course, easy to understand.

von Erica R

Jul 14, 2019

Good overview of the ideas/concepts in data science and the set of courses coming up, but mostly seems to be a place for people to work out any issues getting Git, R, and RStudio set up before they head into the R programming intro. Very light on useful content outside of that. Definitely not 4 weeks worth of course material - can do the whole thing in a couple hours or less.