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The Data Scientist’s Toolbox

Data Science,

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.
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Rating 4.4 based on 4,273 ratings
Length 5 weeks
Effort 1-4 hours/week
Starts Dec 7 (6 weeks ago)
Cost $49
From Johns Hopkins University via Coursera
Instructors Roger D. Peng, PhD, Jeff Leek, PhD, Brian Caffo, PhD
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Mathematics
Tags Data Science Data Analysis Math And Logic

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What people are saying

step by step

Good overview and intro Step by step instructions that have me getting comfortable with coding after a 20 year hiatus.

However, for the students who are really new to coding, courses where creation of git hub account or coding to push/pull data from git hub is involved, i would suggest to add more videos related to step by step coding.

I receive enough step by step information to start something new.

However, you will need to spend more time in CLI and GitHub by looking for information in the forum or googling step by step procedures.

very helpful..teach you step by step There are some typographical errors in the quizzes and the english subtitles.

Excellent course that covers the basics in a very step by step manner.

Good introduction Excellent instruction, step by step coverage of topic in easy to understand terms.

Yet, everything is really presented step by step to make sure that all participants install correctly all tools needed for the further classes included in the specialization.

Good, but would like a step by step walkthrough for MAC/Windows when setting up the final assignment to ensure everything is correct.

I took me step by step, just what I needed since I do not have any previous education in statistics and programming.

It gives the firs tools for data analysis and provides the first tools and how to use them step by step Elementary So far this course is given at a pace that is just perfect.

Walks you step by step getting you setup and familiar with the core software.

It could easily be eliminated Very easy going, but I think week 3 has much information, maybe a step by step toturial might help.

But the step by step instructiona made it easy for me to complete the course succefully.

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command line

Very interesting intro to data science, but the focus on command line Git may drive people away (although it was a great contribution for me!)

You will be learning GitHub, R studio and a bit of command line to be familiar with the tools needed for Data Science.

Should be improved Good general overview and introduction to the command line interface, Git and GitHub.

great course, hope professors talks more about github command line operations.

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.

However, I was not able to co relate the Command Line Interface with the R console after installation.

Very useful, the depth of information was perfect for an introduction to the course This course provide a good introduction to github , Rstudio and command line also gives a information about different ways to analyse data.

Take your time and do the recommended reading and tutorials especially if you are new to Command Line Interface (CLI) Brilliant prep course for what to come from equally well prepared lecturers!

It is also obsessed with command line interfaces.

Love the exposure to Command Line Interface (CLI), Git, Gitbash and R. Will recommend it to anyone that wants a career in any computer/mathematics field.

Although I understand some may need it, the command line course was pretty basic.

The problem was having to work primarily in the command line which provides limited feedback.

Being a developer who has used some of the tools in this toolbox (Git, GitHub, Command Line) this intro really glosses over tools that most non developers won't understand.

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version control

I never gave enough thought to learning basics of version control and git.

In the course you will have some general essential ideas about what is data sciences and which tools are used in the science, and the most importantly, the concept of version control and the GitHub tool for the purpose.

Probably a good course if you aren't terribly familiar with GIT or some form of version control.

I could able to gain the basic knowledge & ideas about tools & questions Data Analysts work with, then could also get practical understanding about the sharing & version control tools.Looking Forward for other Courses.

I would have appreciated more practical experience linking Git and GitHub, as that is critical for version control of code.

You can know about Version Control and Tools like R - Studio.

Great course to get started with R Studio and Version control that actually makes sense.

The git/github version control linking with R/Rstudio is the best thing I got from this caourse.

Nice course to get started in the path to data science with R the course omits some important things like how to download MikTex and how to use it to open an rmd file Learned a lot of really useful stuff about version control with GitHub that I had not encountered in my PhD training , but that seems crucial for industry.

Interesting to learn about version control and utilising Github, which I am sure will be valuable in the future Instructive, well explained.

Good A good introduction to data concepts and the use of version control for projects.

It would have been helpful to have more context or examples for the modules on version control and R Markdown.

and the tools like rstudio and version control is good to know coz it will be used most of the time in the life of a data analyst and data scientist.

Information on Command Line programming and version control with Git and GitHub set-up proving to be useful.

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so far

I am very happy so far!

So far so good.

Very bad course so far.

What I like (so far) is that you have to search for information via internet and by practising your knowledge in GIT and GIThub you can discover what you have learned or what should improve.

Great experience so far, this is my first time in an online course.

I have just started the course but so far the videos and education background references are exceptional.

So far so good, Git was a bit difficult to get going but I'm excited to continue with the specialization.

g Pretty light weight so far, but I certainly understand it's targeted at a broad range of people so the vanilla material is probably a chore for some.

It is a good course and gives a very nice intro to the tools for R. This is a good intro to programming so far.

But I'm very satisfied with the video lecture, and I find it very interesting so far.

So far it is great...just starting week two I ran into a few unexplained issues with final project but a very good course overall.

课程设置得很合理,就是有些细节开展得不够。 Too easy So far this course is pretty amazing.

It is an excellent experience so far Great way to star on the subject, complemented by the book "The elements of data analytic style".Good Job Great intro to the specialization.

mmhmm An excellent introduction for key components of using R Muy bueno el curso So far I'm really enjoying it an find that it is informative Nice and interactive Course Great Introduction Very well explained lectures about key tools used in data science.

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good starting point for

degree, but good for repetition, Git Bash and Github was completely new to me, at the moment I am not 100% sure for what Github and Git Bash are useful, but I am sure I will figure it out in the upcoming courses :) Good starting point for getting familiar with basic tools for data science.

Good Great intro to R programming and how to use github Its a good starting point for Data Science.

very good starting point for people does not have any background in stats and R programming Ce cours est une présentation complete des outils à utiliser et des notions abordées dans le domaine data scientist.

very basic Good starting point for everyone!

It serves as a good starting point for someone getting into the field.

Really good starting point for R Good introductory course.

A good starting point for beginner.

Good starting point for the Data Science This has been a great introduction to the Data Science world.

A good starting point for starting the Data Science carrier!

Good starting point for beginners to learn about R. Basic experience with git is a must although it is possible for complete beginners.

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highly recommended

Highly recommended to those who would like to know and start a career in the data science field.

Highly recommended!

Highly recommended.

Highly Recommended.

Highly recommended for first time learners of R. The git and GitHub section is not very clear....

Highly recommended if you are a beginner.

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) Good overview of the specialization.

It is highly recommended for all who are interested in advancing their careers with Data.

highly recommended for newbs in any kind of development, otherwise waste of time.

Highly recommended Excellent course.

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la ciencia de datos

Nociones básicas de la ciencia de datos.

Very useful introduction about Data Science good begin Es un excelente punto departido para aprender la ciencia de datos.

Buen curso sobre la iniciación a la ciencia de datos, las bases y las herramientas que se emplean para este mundo.

awesome course structure and proper way to begin data science journey with this course El curso muestra un panorama general de la ciencia de datos.

Brinda una introducción a la ciencia de datos (Data Science) y las capacidades de este campo.

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git & github

Great easy introduction on how to get started Could have provided little bit more detail on git & GitHub This is a very good course, very easy to understand and helps a lot to learn how to manage the communities to share data and projects.

A little unclear about the process for using Git & Github.

Pretty good to learn about Git & Github Great introduction to the program!

Good basic foundation for learning how to use online resources like git & github Good course is pretty good but the accent used by instructer should be improved Es un curso para aprender a usar R y RStudio, es útil para poder der mas profesional con tu trabajo, no tiene ejemplos muy desarrollados de la estadística en R pero sigue siendo un buen curso si nunca tuviste una base.

The Git & Github part got me little confusing , a little detailed explanation with live examples would have really helped.

Was a good intro to Git & Github version control through CLI.

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peer review

The final peer review project could have been a little bit more challenging.

Still not sure if it's over or not since i've submitted a peer review assignment and cannot go any further.

Did not like the peer review section.

I just went from showing that I did not pass the peer review section and in the next second was greeted by a big green Course Completion Certificate.

Is this a real course for a data scientist just installing shit and a peer reviewing for that screenshot and forking all repos ...very bad not worth to be with rest course in specialization A really nice overview of tools used in Data Science!

When I contacted the coursera support and asked for help in getting peer reviews they made a change and all my progress was lost.

Peer review was my first experience of this - love the idea!

Good to get an introduction to the process of submitting peer reviewed assignments for future courses.

It is very helpful course Good assignment practice Best courses by coursera well organized, and the peer review is easier than I expected.

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already familiar with

very quick course just to get your workspace set up; if you are already familiar with github or rstudio, no need to check the videos Good at the Beginning level I put three stars because it should be specified more how basic this course is, is almost that this is done for somebody that doesn't know almost anything from CS.

Straightforward (although I am already familiar with markdown and git, so that helps).

Gives you the tools you need to learn the rest of the courses, by itself is completely useless Pretty easy and straight froward, for someone who is already familiar with Programming Editors, and Git shouldn't take 2 hours for him to finish this course including its project, so I guess it's an exciting start for someone who is new for Programming.

infact direct teaching by the instructors is being a good experience rather than using this kind of technologyi reas all the course content, without listening by recorded speech I was already familiar with R and RStudio and found the portion on using Git/GitHub particularly helpful.

I was already familiar with the stuff taught for the most part.

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john hopkins

I am planning to continue to next courses of John Hopkins University.

Clear instructions and well paced This is an amazing course created by John Hopkins.

I found the way in which John Hopkins present the course, very valuable.

Perfect start to a great course.This has to be the best learning experience everMy best regards to the team from John Hopkins great introduction It's a very good course for beginners.

Thanks and John Hopkins University.

Thanks Coursera and JOHN HOPKINS University...... It`s too introductory.

Consecutive course to compliment this would be R programming and Data cleansing and exploratory analysis as in John Hopkins Data Science Specialization Very good.

Thank you coursera and John Hopkins University for providing such a wonderful opportunity to all.

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las herramientas

Para ser una introduccion a las herramientas esta perfecto.

Una introducción interesante y valiosa para los interesados en incursionar y tener a la mano las herramientas básicas de Data Science.

Nos da luces sobre las herramientas que deberíamos usar para optimizar nuestro trabajo (en Big Data) tanto a nivel individual como colaborativo.

Gran Curso te da los conocimiento básicos y las herramientas necesarias para empezar!

Debo decir como profesional de IT que me ha sorprendido cómo empieza desde cero explicando todo lo necesario para entender e instalar las herramientas informáticas necesarias para el curso con un nivel casi de principiante.

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.

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An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Data 1 2 $50k

Data 2 $50k

Environmental Scientists $54k

Clinical Lab Scientists $62k

Outbreak Response Scientists $72k

scientists $88k

Data Analyst, Data Warehousing $93k

Atmospheric Scientists/Physical Oceanographer $103k

Computer Scientists $105k

Data Administrator / Data Modeler $108k

Data Integration Engineer| Data Warehouse $116k

Senior Research Scientists $164k

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Rating 4.4 based on 4,273 ratings
Length 5 weeks
Effort 1-4 hours/week
Starts Dec 7 (6 weeks ago)
Cost $49
From Johns Hopkins University via Coursera
Instructors Roger D. Peng, PhD, Jeff Leek, PhD, Brian Caffo, PhD
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Mathematics
Tags Data Science Data Analysis Math And Logic

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