subject
Intro

Coursera: The Data Scientist’s Toolbox

 with  Jeff Leek
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.

Syllabus

Week 1
During Week 1, you'll learn about the goals and objectives of the Data Science Specialization and each of its components. You'll also get an overview of the field as well as instructions on how to install R.

Week 2: Installing the Toolbox
This is the most lecture-intensive week of the course. The primary goal is to get you set up with R, Rstudio, Github, and the other tools we will use throughout the Data Science Specialization and your ongoing work as a data scientist.

Week 3: Conceptual Issues
The Week 3 lectures focus on conceptual issues behind study design and turning data into knowledge. If you have trouble or want to explore issues in more depth, please seek out answers on the forums. They are a great resource! If you happen to be a superstar who already gets it, please take the time to help your classmates by answering their questions as well. This is one of the best ways to practice using and explaining your skills to others. These are two of the key characteristics of excellent data scientists.

Week 4: Course Project Submission & Evaluation
In Week 4, we'll focus on the Course Project. This is your opportunity to install the tools and set up the accounts that you'll need for the rest of the specialization and for work in data science.

162 Student
reviews
Cost Free Online Course (Audit)
Subject Data Science
Provider Coursera
Language English
Certificates Paid Certificate Available
Hours 1-4 hours a week
Calendar 4 weeks long
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162 reviews for Coursera's The Data Scientist’s Toolbox

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43 out of 46 people found the following review useful
3 years ago
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Life is Study completed this course and found the course difficulty to be very easy.
The Data Scientist’s Toolbox is essentially just an overview of the data science specialization track. It introduces the very basics of R and R studio, Git and Github and a few other things that will be used in the data science specialization track. It is basically a bunch of introductory and supplementary material tha Read More
The Data Scientist’s Toolbox is essentially just an overview of the data science specialization track. It introduces the very basics of R and R studio, Git and Github and a few other things that will be used in the data science specialization track. It is basically a bunch of introductory and supplementary material that shouldn't be a standalone course. You can complete all the lecture videos in the entire course in about 2 hours. It's almost embarrassing that John Hopkins has a paid verified certificate option for this course and it is required to complete the data science specialization track.
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37 out of 41 people found the following review useful
3 years ago
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Anonymous completed this course.
The whole "course" is doable in about 2 hours. It's laughably easy − the main point is to get you to install RStudio. Granted, if you've never used Github it'll be a bit bewildering, but I think it's wildly excessive to have a Signature Track certificate with a $49 fee to basically prove you're capable of signing up to a website.
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1 out of 1 people found the following review useful
a year ago
Brandt Pence completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
This is the first course in the Data Science specialization, offered by Johns Hopkins through Coursera. The official schedule lists the time commitment as 4 weeks of study with 1-4 hours/week of work. In reality, this course can be easily completed in a few hours by anyone with a reasonable background in computers. Mos Read More
This is the first course in the Data Science specialization, offered by Johns Hopkins through Coursera. The official schedule lists the time commitment as 4 weeks of study with 1-4 hours/week of work. In reality, this course can be easily completed in a few hours by anyone with a reasonable background in computers. Most of the course is dedicated to installing programs like RStudio, which is less-than-helpful for most users. However, for those unfamiliar with Git and GitHub, the introductory lectures on those topics are reasonably valuable, although there are better introductions available elsewhere.

Overall, this course is probably not even worth the $29 currently charged, but it is a required part of the specialization and thus necessary for those planning to complete it. For others, it may be a better use of time to simply download Git, R, and RStudio and to set up a GitHub account, then to move directly to R Programming. For those on the specialization track, this course can be easily completed in one night, and there should be no problem starting R Programming concurrently with this course.

The final project asks you to submit a screenshot to prove you can install and open RStudio, and to do a few simple tasks in GitHub (create a repo, create and push a markdown file to that repo, and fork someone else’s repo). The assignment is peer-graded, which historically has been a cause for concern in many of the Data Science track courses, but the questions are yes/no and straightforward enough that they leave little to a fellow student’s (sometimes rather skewed) interpretation. For example, a forum post early in the course asked if it would be preferable to reserve perfect scores on the peer-based assignment for students who had “exceeded the requirements” for the final project. Fortunately, this idea was shot down by subsequent posters (and it’s not realistically possible for this assignment anyway), but it displays a mentality that may cause good students to lose points unfairly in later classes. Reviews from other former students available online suggest that this is an ongoing problem.

Overall, two stars, mostly for the Git and GitHub material to which I had not been previously exposed.
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17 out of 21 people found the following review useful
3 years ago
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Ricardo Vladimiro completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
This is a very simple introductory course of Coursera's Data Science Specialisation. It gives a brief overview of the eight other courses in the specialisation, an overview of what data science is (in the instructors opinion) and an overall crash course on R, RStudio and Github. The course is a blessing if you don't Read More
This is a very simple introductory course of Coursera's Data Science Specialisation.

It gives a brief overview of the eight other courses in the specialisation, an overview of what data science is (in the instructors opinion) and an overall crash course on R, RStudio and Github.

The course is a blessing if you don't have any coding or computational statistics background since it is an appropriate introduction. If you have the background are taking the course for the specialisation sake, it is annoying but you can do it in (literally) 4 hours.
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9 out of 10 people found the following review useful
3 years ago
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Anonymous completed this course.
Okay...so this course is easy and can the whole project can be completed within a couple hours. Even so, this is a valuable and helpful course for those new to Github, R, and some statistics jargon. I agree with many other reviewers that this course definitely isn't worth the $49 fee for the verification services. Ev Read More
Okay...so this course is easy and can the whole project can be completed within a couple hours. Even so, this is a valuable and helpful course for those new to Github, R, and some statistics jargon.

I agree with many other reviewers that this course definitely isn't worth the $49 fee for the verification services. Even newcomers will quickly realize that this course is ridiculously easy and lacking in fruitful rewards of useful knowledge. I would really like to see this course's verified certificate be offered at a lower price, if not offered for free since the work isn't difficult.

Don't let the reviews of this course serve as the general impression of the rest of the Data Science courses. The later courses involve much more work and expose students to truly rewarding knowledge and skills such as basic statistics and programming.
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16 out of 17 people found the following review useful
2 years ago
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Anonymous completed this course.
Your reaction to this course will likely depend on your background. If you already know about integrated programming environments (RStudio), version control (git and github), and mark-up languages (markdown and knitr) you will find it insultingly simple. If you don't know what I'm talking about, you badly need to do th Read More
Your reaction to this course will likely depend on your background. If you already know about integrated programming environments (RStudio), version control (git and github), and mark-up languages (markdown and knitr) you will find it insultingly simple. If you don't know what I'm talking about, you badly need to do this course before attempting the rest of the specialisation. As a once upon a time programmer who has not kept up, I found it fairly easy but also very useful.
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8 out of 9 people found the following review useful
2 years ago
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Anonymous completed this course.
This class should be both: - optional. - free. Instead, it's required, and I wasted money paying for it. Others have covered this class's material in their reviews. My two cents are, this content is insultingly simple if you have a decent amount of experience as a programmer. (I'm in the "danger zone" of their da Read More
This class should be both:

- optional.

- free.

Instead, it's required, and I wasted money paying for it.

Others have covered this class's material in their reviews. My two cents are, this content is insultingly simple if you have a decent amount of experience as a programmer. (I'm in the "danger zone" of their data scientist venn diagram, I guess). It is literally painful to sit through an "introduction to the command line" after many years working in Unix.

It's inappropriate to place course overviews behind a paywall. I would not have paid the (now-reduced) $29 for this course if it weren't a gateway to the later ones.
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6 out of 7 people found the following review useful
3 years ago
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Jasmine Mercier completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
This course provides a useful introduction to Git, GitHub, R, and RStudio, which are all very useful tools you'll need to complete the rest of the specialization as well as in real data science work. It also provides a philosophical overview of just what "data science" is all about, clarifying what kinds of work actual Read More
This course provides a useful introduction to Git, GitHub, R, and RStudio, which are all very useful tools you'll need to complete the rest of the specialization as well as in real data science work. It also provides a philosophical overview of just what "data science" is all about, clarifying what kinds of work actual data scientists do.

Unfortunately, all the material can be covered in a single day. The class should really have been a part of the R Programming course - paying $50 for the signature track (if you plan on doing the capstone project for the specialization) seems a bit too much.
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15 out of 17 people found the following review useful
3 years ago
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Mohamed Sameh completed this course and found the course difficulty to be very easy.
The course is very easy, and its material is very shallow, it should have been only a first-week introduction to another course in Coursera's Data specialization track.
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5 out of 6 people found the following review useful
3 years ago
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Greg Chapman completed this course, spending 3 hours a week on it and found the course difficulty to be very easy.
First, I should note that the time spent per week is actually the total time for completion. This course is a very straightforward introduction to the data science track and the tools that are going to be used in the rest of the track. And that's it, there's really no meat to this course, but if you're not familiar w Read More
First, I should note that the time spent per week is actually the total time for completion. This course is a very straightforward introduction to the data science track and the tools that are going to be used in the rest of the track. And that's it, there's really no meat to this course, but if you're not familiar with Git or command-line interfaces it could be really helpful. I suppose if you're paying for the specialization you just have to amortize the cost of this course over the other courses in the track.
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9 out of 10 people found the following review useful
3 years ago
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Anonymous completed this course.
If you have never worked with Git, GitHub, R, or RStudio, this is a great (very short) introduction.

I have seen a lot of people in later courses of the specialization complain that they did not know how to upload the peer projects onto github, so I would say it can be a very useful class.
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3 out of 3 people found the following review useful
2 years ago
Adelyne Chan completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
A very simple introduction to the tools used in data science, mainly to get students acquainted with using GitHub repositories and RStudio. I took this because it was recommended for the other courses in the specialisation, but if you are comfortable with using virtual tools it is probably possible to learn on the job Read More
A very simple introduction to the tools used in data science, mainly to get students acquainted with using GitHub repositories and RStudio. I took this because it was recommended for the other courses in the specialisation, but if you are comfortable with using virtual tools it is probably possible to learn on the job with the subsequent courses. This course could feasibly be completed in a single sitting.

Although I intend to take all the courses in the specialisation for its content (thus did not pay for a Verified Certificate), I am aware that a number of other people who are taking this for the specialisation did feel that it was not worth the money they paid given the very little content covered.
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7 out of 10 people found the following review useful
3 years ago
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Anonymous is taking this course right now.
Very difficult if you don't have any prior programming and computer science knowledge. This is not a beginners course. Frustrating, challenging, assumes students have enough prior knowledge to fill in the gaps during the lectures. As someone with no prior computer experience of any kind (other than basic Word) I was lost almost immediately.
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4 out of 4 people found the following review useful
2 years ago
Matteo Ferrara completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
By far the worst course ever taken. I understand they need to find a viable business model, but if I did not take courses on Coursera before it, I would have not bother to open Coursera again. It is even worse since their following course, introduction to R, has a very steep learning curve (let alone it is as well a ve Read More
By far the worst course ever taken. I understand they need to find a viable business model, but if I did not take courses on Coursera before it, I would have not bother to open Coursera again. It is even worse since their following course, introduction to R, has a very steep learning curve (let alone it is as well a very bad course compare with the rest of Coursera offer), they could have put all together in one course, one week for this and 7 for R, instead of 4 and 4.
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2 out of 2 people found the following review useful
2 years ago
Ryan Bowen completed this course, spending 2 hours a week on it and found the course difficulty to be very easy.
This course essentially is just a walkthrough of the different programs that you will be utilizing throughout the rest of the Data Science Specialization (if you are continuing with the other courses). The fact that they allow you to pay for this course is a joke because you are taught next to nothing except how to ins Read More
This course essentially is just a walkthrough of the different programs that you will be utilizing throughout the rest of the Data Science Specialization (if you are continuing with the other courses). The fact that they allow you to pay for this course is a joke because you are taught next to nothing except how to install programs. If you plan on finishing the entire Specialization, then perhaps paying for it will benefit you in the long run. Otherwise, the class is easy, does not take much time, and sets you up to continue with the other courses.
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2 out of 3 people found the following review useful
2 years ago
Krishna Magar completed this course.
Great course if you are hearing the words GitHub, R and RStudio for the first time. It will provide you the basics(practically) of these terms and rest of the courses in the Specialization. For people like programmers, it's just a mode of entry(only with the payment) to the rest of the Specialization courses. So, it's Read More
Great course if you are hearing the words GitHub, R and RStudio for the first time. It will provide you the basics(practically) of these terms and rest of the courses in the Specialization. For people like programmers, it's just a mode of entry(only with the payment) to the rest of the Specialization courses. So, it's painful that this 2 hrs course is expanded to a month plus a fee. But then its a good bargain for the ovearall courses in Specialization. Cheers !
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3 out of 3 people found the following review useful
2 years ago
Guest partially completed this course.
Taking this course was very annoying due to it's lack of structure(specifically when the quizzes should be taken) & shallow content (mostly overviews). Also if you have an older computer installing to software needed to complete the class maybe a challenge. I may try it again when I need a new computer.
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2 out of 3 people found the following review useful
2 years ago
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Greg Kent completed this course, spending 2 hours a week on it and found the course difficulty to be easy.
Overall, the class is pretty simple, and far easier than the other classes in this specialization. Really, the hardest part of this course was finding the complete instructions for the final project. The first part was found easily enough, but the other parts of the project are not obvious.
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2 out of 3 people found the following review useful
2 years ago
Terrel Shumway completed this course, spending 2 hours a week on it and found the course difficulty to be very easy.
The course was a good introduction. As an experienced programmer, I found the course quite easy. However, I do appreciate the focus on setting up the tools and environment. Too many people leave version control to chance. It is something people are just supposed to pick up as they go along.
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2 out of 2 people found the following review useful
2 years ago
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Anonymous completed this course.
Eh. I wasn't really impressed with the presentation. It's too low a level if you've had any experience at all and it isn't a particularly good explanation if you've never seen this stuff before. I will try the R class at this point but I am already shopping around for alternatives.
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3 out of 4 people found the following review useful
2 years ago
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Frans Werrij completed this course, spending 5 hours a week on it and found the course difficulty to be medium.
When you spend your time every week, submit the weekly quizzes and the final project this course is worthwile as a start of the Data Scientist specialization. I enjoyed it.
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4 out of 6 people found the following review useful
2 years ago
Maboroshi completed this course, spending 1 hours a week on it and found the course difficulty to be easy.
Very easy course. Just set up your github account, and you are done! This course could have been combined with other courses.
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3 out of 3 people found the following review useful
3 years ago
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Anonymous completed this course.
This course is fairly weak. It might be interesting if you really have no idea about Data Science, but if you have any knowledge you might find far too obvious.
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2 out of 2 people found the following review useful
2 years ago
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Anonymous completed this course.
The course was as expected, given its description in Coursera.

I found the exercises very easy. I don't think it makes sense to enroll unless you're aiming at the data science specialization.
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2 out of 2 people found the following review useful
2 years ago
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Ramesh Natarajan completed this course, spending 2 hours a week on it and found the course difficulty to be easy.
This course provides a catalog of tools for subsequent courses in this set (eg: GitHub, RStudio, etc). Its a pretty decent introduction even if you want to get stared with R programming.
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2 out of 3 people found the following review useful
2 years ago
Cláudio Tereso completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
What a deception, just a couple of exercises on Github. Why do they make us pay for this? A very bad introduction to the "Data Science" specialization.
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1 out of 1 people found the following review useful
2 years ago
Chris Rodger completed this course, spending 1 hours a week on it and found the course difficulty to be easy.
The course was fine -- it was really an intro in the sense of just having you set up accounts and various software. The bulk of the time is spent listening to the lectures. It probably isn't a month's worth of material.
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1 out of 1 people found the following review useful
3 years ago
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Anonymous completed this course.
Strange class as in there is very little content. Basically, the instructors want you to install GitHub and R Studio and learn a few basic terms and ideas about data science.
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2 out of 2 people found the following review useful
2 years ago
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Anonymous completed this course.
This is a joke, not a course. A way to make money for JHU. Total scam. There's literally about an hour of work in this course.
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1 out of 1 people found the following review useful
2 years ago
Balagopal K S completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
Teaching was good but too less content for a course. Very basic stuff that one can just read and understand in little time.
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a year ago
Adia Alderson completed this course, spending 2 hours a week on it and found the course difficulty to be very easy.
Its a good course and went at a great pace. The course structure basically just gets all the base tools set up you will need to finish the Data Science Specialization and then an overview of the concepts you will learn in it. So think of this as an overview and prep before diving into the main part of the specializatio Read More
Its a good course and went at a great pace. The course structure basically just gets all the base tools set up you will need to finish the Data Science Specialization and then an overview of the concepts you will learn in it. So think of this as an overview and prep before diving into the main part of the specialization track.

Although if you're familiar with the toolset or have some exposure to data science then I would skip this one. Sadly it's part of the track for specialization, I feel it should be optional. Although for the absolute beginner it's essential. Also, some of the videos were a bit long. I feel maybe some comprehension checks to break it up would be nice.
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3 out of 7 people found the following review useful
3 years ago
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Scott Orr partially completed this course.
Much of The Data Scientist's Toolbox is devoted to introducing the topics of the specialization's other eight courses; frankly, you can skip this if you don't intend to take those courses . For me, the most useful content of this class was its introductions to Git, GitHub, and RStudio (I had been using the plain old R Read More
Much of The Data Scientist's Toolbox is devoted to introducing the topics of the specialization's other eight courses; frankly, you can skip this if you don't intend to take those courses . For me, the most useful content of this class was its introductions to Git, GitHub, and RStudio (I had been using the plain old R Console, and RStudio makes things considerably easier). RStudio is required for the programming necessary to complete the assignments in the later courses, and Git and GitHub are necessary to complete the projects at the end of each course (you have to upload your work to GitHub so that other students can peform peer assessments on it).
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2 years ago
Thomas Ploch completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
For programmers with even only a little bit of experience this course is a no-brainer. But I agree with other commenters here that if you had no programming background, then this course is a must. It introduces beginners into fundamental concepts such as Version Control and Markdown and prepares for the rest of the specialization.
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2 years ago
Jaron Hightower-mills completed this course.
This course gives you a great introduction to the overall concepts of data science and the tools that you will need to use in the other courses in the certificate sequence. Given that I have struggled with other stats-related courses on Coursera, I truly appreciated the tutorial style of this first course.
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11 months ago
Deanne Ridge is taking this course right now and found the course difficulty to be medium.
I've just begun this course so I don't know how much time I will spend each week but it is definitely holding my interest. It is great because it's an entry level course to a complex subject. It has free tools and they instruct you in getting set up.
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a year ago
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Cameron completed this course, spending 2 hours a week on it and found the course difficulty to be medium.
Learned a bit but overall it is literally not worth the price of admission. I think that this course could be offered for free and maybe the others are worth paying for. Hope that the rest of the specialization is worthwhile
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a year ago
Daniel Rosquete completed this course, spending 4 hours a week on it and found the course difficulty to be very easy.
Well, this course is nice for beginners, specifically those who don´t have a clue about R language.

For those who already knew R and a little bit of github, is just a couple of hours of lectures and that will be it
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a year ago
Robert Stahr completed this course, spending 2 hours a week on it and found the course difficulty to be easy.
OK Course. What bothered me most was that you do not see the instructor for most of the course. You just see the slides and hear a voice. And one instructor hadn't prepared well so it was awful to listen to.
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a year ago
Snivy completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
The course content is more like a prerequisite for the first week of a real course. There's nothing to it, even if you're a complete beginner, you can complete this in a couple of hours.
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9 months ago
Omar F. completed this course and found the course difficulty to be easy.
I only recall that the course was fairly straightforward, but a good intro to the specialization. I would only recommend this if you're planning to complete the Data Science specialization.
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a year ago
Jason Michael Cherry completed this course, spending 2 hours a week on it and found the course difficulty to be very easy.
This is really just a primer course for the following courses in the specialization. If you're familiar with R and Git/Github already, you can skip it easy.
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2 months ago
Jeff Potoski partially completed this course and found the course difficulty to be medium.
Too much theory. Some of the practices seem the little bit outdated. Maybe it's not a bad course. But I believe you can find better recourses to spend time on.
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3 out of 3 people found the following review useful
3 years ago
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Anonymous completed this course.
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2 years ago
Doris Smith completed this course, spending 2 hours a week on it and found the course difficulty to be easy.
Very basic: its role seems to be simply to prepare the student for other classes in the Data Science specialization.
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1 out of 1 people found the following review useful
2 years ago
Christopher X Gerber is taking this course right now.
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2 years ago
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James Porter completed this course.
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a year ago
Mark Round partially completed this course.
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3 years ago
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Matthew Honeyman completed this course, spending 1 hours a week on it and found the course difficulty to be very easy.
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2 years ago
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Renato Feijó Da Rocha completed this course, spending 4 hours a week on it and found the course difficulty to be medium.
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Na'the Clemence is taking this course right now, spending 2 hours a week on it and found the course difficulty to be easy.
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Kuhnrl30 completed this course and found the course difficulty to be very easy.
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Alex dropped this course, spending 10 hours a week on it and found the course difficulty to be very hard.
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