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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 4.3 based on 2,928 ratings
Length 5 weeks
Effort 1-4 hours/week
Starts Oct 5 (3 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

data science specialization

good explanation I think it is a good introduction to the data science specialization.

This basic one is very important for later study because "Grinding a chopper will not hold up the work of cutting firewood" : ) this part is not necessary, keep it optional please I personally think that this course should be better interwoven into the other modules of the data science specialization.

As someone new to data science this course provided a simple, yet firm and comprehensive foundation for the rest of the courses in the data science specialization.

Good introduction on Data science specializationi.

VERY GOOD Its really helpful This course was a quick and easy introduction to the Data Science Specialization.

I trust that the other courses that constitute the whole Data Science Specialization series will dive deeper into the individual subjects.

Good to begin with data science This was a great opening course for the Data Science specialization because it talked about the tools that will be used to illustrate the concepts that are coming later.

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looking forward

Looking forward to going deeper.

Looking forward to the next course!

Looking forward to the rest of the courses in the Specialization!

I am looking forward to taking the other courses related to Data Science.

Looking forward to the next courses.

I give 5 stars to the course because it offers different perspective to my current job and I'm looking forward to learn more to the upcoming modules.

Useful and interacti Very satisfied with the way course was delivered and looking forward to the other classes in the course.

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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.

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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.

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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.

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good starting point

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 starting point Algumas informações estão desatualizadas o que dificulta o aprendizado.

it was a good starting point for may training I really benefit a lot for the course! Great introductory course for Data Science.

Excellent course gives you a lot pf tools to face the changing world very good Good starting point, tool download, etc.

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.

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Careers

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 4.3 based on 2,928 ratings
Length 5 weeks
Effort 1-4 hours/week
Starts Oct 5 (3 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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