What are MOOCs?

How do I register?

To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.

How do these MOOCs or free online courses work?

MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.

21 out of 21 people found the following review useful

3 years ago
**completed** this course.

Duke’s Data Analysis and Statistical Inference on Coursera is an introduction to statistics with an optional computational component using the R programming language. The course runs about 8 weeks and covers a considerable amount of ground in that time. It starts with the basics of data and data collection methods but
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Duke’s Data Analysis and Statistical Inference on Coursera is an introduction to statistics with an optional computational component using the R programming language. The course runs about 8 weeks and covers a considerable amount of ground in that time. It starts with the basics of data and data collection methods but quickly moves on to cover probability, the normal distribution, the binomial distribution, hypothesis testing, confidence intervals, Z and T statistics, ANOVA and Chi squared tests and linear regression. The course is a bit of a whirlwind tour that packs a lot into each lecture. The PDF slides that go along with the videos are a great resource to review the information dumped in each lecture. Many students complained that the course requires more time than the original estimated amount of around 6-8 hours per week. The course was later updated with an estimate of 8-10 hours per week, which is on the conservative side. If you come in with some prior knowledge of stats and R you can get through in 3-5 hours per week.

The professor is engaging and does a good job going through the material while providing adequate face time. The slides are very informative and the video quality is excellent. There are periodic in-lecture quizzes that help test your understanding of the material as you go along. I felt that the frequency of in-lecture quizzes was just about right in this course.

The professor is engaging and does a good job going through the material while providing adequate face time. The slides are very informative and the video quality is excellent. There are periodic in-lecture quizzes that help test your understanding of the material as you go along. I felt that the frequency of in-lecture quizzes was just about right in this course.

10 out of 10 people found the following review useful

3 years ago
**completed** this course.

Great, great course. A well balanced mixture of theory, examples, labs and to learn software and projects to test your skills in the 'real' world.
The teacher explains the concepts very clearly. The course layout and order of topics is excellent. The difficulty is does not change overall. The free and open textbook is
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Great, great course. A well balanced mixture of theory, examples, labs and to learn software and projects to test your skills in the 'real' world.

The teacher explains the concepts very clearly. The course layout and order of topics is excellent. The difficulty is does not change overall. The free and open textbook is the best I've come across. It is packed with footnotes to datasets, and has more than enough examples and exercises to get you through the midterm and the exam.

The teacher is very active on the forums and even organised a Google hangout session you can join.

The focus of this course is definitely not on mathematical proofs, probability theory or working through problems analytically, but geared towards practical approaches using given formula's or R to get results on every day problems.

Integrated into the course is the datacamp environment that helps you to learn the software R by playing with data. The nature of these task mirror the theory discussed that week. There are some glitches in this new environment (during the first run of this course), and the tasks are not really challenging.

The quizzes are quite good. Many of the questions test your insight rather than ask you to do tedious algebra.

The peer reviewed research projects are time consuming, great fun and an excellent way to get your hands wet with real data, R and doing some real data analysis.

One of the best courses I've taken.

The teacher explains the concepts very clearly. The course layout and order of topics is excellent. The difficulty is does not change overall. The free and open textbook is the best I've come across. It is packed with footnotes to datasets, and has more than enough examples and exercises to get you through the midterm and the exam.

The teacher is very active on the forums and even organised a Google hangout session you can join.

The focus of this course is definitely not on mathematical proofs, probability theory or working through problems analytically, but geared towards practical approaches using given formula's or R to get results on every day problems.

Integrated into the course is the datacamp environment that helps you to learn the software R by playing with data. The nature of these task mirror the theory discussed that week. There are some glitches in this new environment (during the first run of this course), and the tasks are not really challenging.

The quizzes are quite good. Many of the questions test your insight rather than ask you to do tedious algebra.

The peer reviewed research projects are time consuming, great fun and an excellent way to get your hands wet with real data, R and doing some real data analysis.

One of the best courses I've taken.

8 out of 8 people found the following review useful

2 years ago

I've had plenty (cough) of time to forget the basic statistical inference I did at high school. This was a great refresher (if a little repetitive - hypothesis tests vary mainly in relatively minor-seeming details). With a little prior exposure, it's not too time consuming. But at the same time it never degenerated - i
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I've had plenty (cough) of time to forget the basic statistical inference I did at high school. This was a great refresher (if a little repetitive - hypothesis tests vary mainly in relatively minor-seeming details). With a little prior exposure, it's not too time consuming. But at the same time it never degenerated - in the way of much stat inf pedagogy - into a pure exercise in plugging numbers into formulae; some questions were demanding enough to require significant headscratching and envelope scribbling

And judging by the quality of the materials (video, detailed learning objectives plus references to an open textbook - more or less optional given the copious lecture material and summary "learning objectives") & reactions in the forums, it's a great introduction for people without previous exposure to the topic, with the added bonus of a gentle introduction to R (via the excellent datacamp website should you prefer).

Thanks to Dr Mine, there is now no excuse for statistical illiteracy.

No.

Ex.

Cuse.

(Update: DASI has two tracks - with and without a project and R labs. The project is supposed to be necessary for a distinction, but I just discovered that with a high enough grade on the exams/quizzes, it isn't :)

And judging by the quality of the materials (video, detailed learning objectives plus references to an open textbook - more or less optional given the copious lecture material and summary "learning objectives") & reactions in the forums, it's a great introduction for people without previous exposure to the topic, with the added bonus of a gentle introduction to R (via the excellent datacamp website should you prefer).

Thanks to Dr Mine, there is now no excuse for statistical illiteracy.

No.

Ex.

Cuse.

(Update: DASI has two tracks - with and without a project and R labs. The project is supposed to be necessary for a distinction, but I just discovered that with a high enough grade on the exams/quizzes, it isn't :)

3 out of 3 people found the following review useful

3 years ago
**completed** this course.

Extremely time consuming. I work in a market research firm, have some familiarity, and perhaps because of that some misconceptions. The course is very very well organised by the instructor, much of the material follows each other, so no time wasted like some other online courses. Believe me you'll need every extra minu
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Extremely time consuming. I work in a market research firm, have some familiarity, and perhaps because of that some misconceptions. The course is very very well organised by the instructor, much of the material follows each other, so no time wasted like some other online courses. Believe me you'll need every extra minute. Her videos are upbeat as well, never a dull moment. One thing make sure your math skills are up to par. My math skills need brushing up, but I'm used to data and programming so that took the edge off. I would say make sure you have the rest of your life organised while doing the course. Definitely worth every aching minute though.

4 out of 4 people found the following review useful

2 years ago

One of the greatest courses I've taken so far. A great teacher, very much involved in exchanges with her students. A large variety of teaching approaches and tools. Lots of practice, through short tests, R-programming labs, and an in-depth project. A very lively forum, with lots of help to cope with difficulties. The c
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One of the greatest courses I've taken so far. A great teacher, very much involved in exchanges with her students. A large variety of teaching approaches and tools. Lots of practice, through short tests, R-programming labs, and an in-depth project. A very lively forum, with lots of help to cope with difficulties. The course is not too difficult, but the variety of the proposed material requires that students get involved quite substantially. A very nice book available for free, with plenty of practice exercises.

2 out of 4 people found the following review useful

2 years ago
is taking this course right now.

i have completed 5 weeks so far. and now i am dropping out of this course. its painfully slow and easy. I was looking to gain more knowledge on stats before i stats my ms program in analytics. I dont want to take away the credits from duke uni or Dr Mine Rundel. She has done great work . I went through her book os and
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i have completed 5 weeks so far. and now i am dropping out of this course. its painfully slow and easy. I was looking to gain more knowledge on stats before i stats my ms program in analytics. I dont want to take away the credits from duke uni or Dr Mine Rundel. She has done great work . I went through her book os and read pdfs. this way i saved time. but now i am dropping out. ( I am from engineering background )

4 out of 4 people found the following review useful

3 years ago
**completed** this course.

Time consuming, but this course is well worth the money on signature track! This will give you a very solid understanding of statistic, which is the basic of so many other fields: experimental research, lean, and machine learning just to name a field.

Unmissable if you want to broaden your knowledge on how to do things with scientific rigor.

Unmissable if you want to broaden your knowledge on how to do things with scientific rigor.

3 out of 3 people found the following review useful

3 years ago
**completed** this course.

This course has a fairly high standard for passing (80%). Though this can be frustrating, it ultimately drives you to buckle down and learn the material. Those who cannot devote a decent amount of time to the course will feel lost if they have no former introduction to the topic. If you can devote the time, it is rewarding and very well taught. Highly recommended.

2 out of 3 people found the following review useful

3 years ago
is taking this course right now.

This is definitely the best Coursera course I have ever done (and probably best MOOC). Very high quality materials, presented and explained extremely well and with a lot of real world practical examples which most stats courses do not have. It is a high workload and a high pass mark but you will get real, useful knowledge

2 out of 3 people found the following review useful

a year ago

Very time consuming course still doesn't contain any proofs. All the time spent just to make you memorise quite simple concepts but not to understand why do they work.

Don't wast your time, go through book and pdf slides and you will end up with the same knowledge many times faster.

Don't wast your time, go through book and pdf slides and you will end up with the same knowledge many times faster.

2 out of 2 people found the following review useful

3 years ago
**completed** this course.

Thisi is one of the best course I ever took online or at university.

The content is challenging but the professor explains it so well that it is a pleasure to come back for more every week.

Its not easy, you have to work a lot to succeed but if you do, you will be very happy with this class.

The content is challenging but the professor explains it so well that it is a pleasure to come back for more every week.

Its not easy, you have to work a lot to succeed but if you do, you will be very happy with this class.

1 out of 1 people found the following review useful

2 years ago
**completed** this course.

One of the very best courses - instructor was engaging, course material was challenging but extremely interesting. I find myself referring to this material repeatedly in my data science work.

1 out of 1 people found the following review useful

4 months ago

Dr.Mine is one of the best professors I've known. She can communicate arcane concepts very effectively and her passion is seen in every lecture.

3 days ago
**completed** this course.

I took this course a while back before it changed format. From the other reviews, I see that that it is still a great course. I had no background in statistical inference but lots in programming before taking the course so the R programming was fairly trivial and I could concentrate on learning data analysis and statis
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I took this course a while back before it changed format. From the other reviews, I see that that it is still a great course. I had no background in statistical inference but lots in programming before taking the course so the R programming was fairly trivial and I could concentrate on learning data analysis and statistical inference. The material was presented methodically and with many worked examples. This is not a 'fast-paced' course. If you need to cram material, this isn't the right course for that. This course teaches you the language of the scientific method - how to articulate a hypotheses that can be disproven. Like any language, the art of speaking it takes time and practice.

2 years ago

Took the course,finished it but didnt pass,as igot a really bad grade in the midterm.The course is probably the best introductory-intermediate course available.Together with the book (Open Intro) makes a perfect start for anyone who wants to get serious with statistics.Time consuming,you really have to allow for lots o
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Took the course,finished it but didnt pass,as igot a really bad grade in the midterm.The course is probably the best introductory-intermediate course available.Together with the book (Open Intro) makes a perfect start for anyone who wants to get serious with statistics.Time consuming,you really have to allow for lots of work and lots of reasoning,as exercises tend to be with lengthy descriptions,and the quizzes too. In all a pleasant experience (it would have been better if i d passed :):))...I seriously reccomend it,and i am waiting for the next iteration ,in order to gain the certificate,which i consider a valuable addition to anyone's skill kit.

2 years ago

A wonderful course on data analysis and statistical inference as well as the use of R (and R Studio, although there is the option for students to complete the assignments online using a DataCamp platform). I found the exercises and especially the project an extremely interesting endeavour, and the provision of an open-
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A wonderful course on data analysis and statistical inference as well as the use of R (and R Studio, although there is the option for students to complete the assignments online using a DataCamp platform). I found the exercises and especially the project an extremely interesting endeavour, and the provision of an open-courseware textbook is a very nice gesture by the instructor.

For other learners, particularly those who are not particularly after a certificate and don't want to wait till the next offering of the course, it is also possible to cover the same course material through the DataCamp platform at your own leisure!

For other learners, particularly those who are not particularly after a certificate and don't want to wait till the next offering of the course, it is also possible to cover the same course material through the DataCamp platform at your own leisure!

a year ago

One of the best MOOCs out there, not really much to say besides that. Very time consuming if you choose to join the track with programming assignments. However, they are totally worth your time. The recommended exercises are also useful, and the final project was interesting as well. It's just the perfect MOOC (for me, at least).

2 years ago

Very good practical oriented course. All concepts clearly explained. Many useful examples from real world are demonstrated in detail. Flow is very smooth from basic to advanced topics.

0 out of 1 people found the following review useful

0 out of 1 people found the following review useful