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Learner Reviews & Feedback for Mastering Data Analysis in Excel by Duke University

3,909 ratings

About the Course

Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. Your first model will focus on minimizing default risk, and your second on maximizing bank profits. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model. The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. Your role as a data-analyst is to reduce uncertainty for decision-makers by a financially valuable increment, while quantifying how much uncertainty remains. You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classification error rates, entropy of information, and confidence intervals for linear regression. All the data you need is provided within the course, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. The course will give you enough practice with Excel to become fluent in its most commonly used business functions, and you’ll be ready to learn any other Excel functionality you might need in the future (module 1). The course does not cover Visual Basic or Pivot Tables and you will not need them to complete the assignments. All advanced concepts are demonstrated in individual Excel spreadsheet templates that you can use to answer relevant questions. You will emerge with substantial vocabulary and practical knowledge of how to apply business data analysis methods based on binary classification (module 2), information theory and entropy measures (module 3), and linear regression (module 4 and 5), all using no software tools more complex than Excel....

Top reviews


Nov 16, 2021

I like and appreciate courses provided through Coursera.This course is very interesting and valuable for those whose jobs do have relevance with data management .God bless Coursera and Duke University


Oct 30, 2015

The course deserves a 5-star rating because: (1) content is relevant, (2) the professor is concise and possesses great teaching skills, and (3) the learning modules are applicable to daily problems.

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26 - 50 of 934 Reviews for Mastering Data Analysis in Excel

By Ian B

Apr 3, 2021

This course contains very minimal instruction in Excel skills beyond the basics, as it is really just a math course consisting almost entirely of plugging values into premade spreadsheets. This would perhaps be forgivable if it were a decent math course, but that is also not the case. Lecture videos are low quality, littered with confusing errors and there is even a mistake in a graded quiz that remains uncorrected long after being brought to the attention of course staff. The final assignment is so poorly explained and confusing that extensive use of peer advice from forums is needed. It is obvious from the poor quality of this course that the instructor and staff have little respect for students' time and learning experience.

Plagiarism and requests for quid-pro-quos appear to be rampant in the final assignment, and peers grade assignments incorrectly and arbitrarily even when provided answers explicitly match the criteria of the grading rubric, so expect your grade to have little connection to the correctness of your assignment or how much effort you spend on it. It's essentially a dice roll whether you receive graders capable of understanding the rubric and/or willing to take the time to accurately assess your work.

I spent many hours completing this course in earnest and I wish I could have that time back to apply to more valuable courses. I will not be continuing with this Specialization or taking any additional courses from Duke on Coursera and I recommend anyone considering this course or others in the Specialization to look elsewhere.

By Jason T

Jun 12, 2017

This was more a statistics course than a

By Paul J H L

Feb 24, 2016

This is my first Coursera course and I wasn't sure what to expect. I was hoping for a good experience but preparing myself for mediocrity.

I finished the course at 2am on Monday morning and I've been really impressed, both with the Coursera "infrastructure" and with the quality of the teaching from Daniel Egger and his team. I live in South Africa where tertiary educational standards vary widely, and appear to be on the decline. More and more, we are going to need MOOCs like this from the best universities in the world.

More specifically, relating to this course, I found the video lectures well presented and the quizzes thoughtfully prepared. The Excel models really helped with grasping the concepts and practice.

A couple of suggestions:

a) The course FAQ makes light of the background knowledge necessary to cope with the course. It needs to be more honest about the need for mathematics and statistics. Linear regression is not for sissies, in my opinion.

b) Please tell us at the START of the course that we should attack the project week by week. This advice isn't (unless I missed something) given until you open the week 6 project. Ahem... it's too late by then! I spent a very frantic 4 nights last week crunching the project work, 4 quizzes and the assignment. I got to bed at 2.30am, and i'm not a night owl.

Overwhelmingly though, a really interesting course. I'm already starting the next one.

By Davis L

Oct 11, 2017

The class could be better

By Steven T

Dec 2, 2015


By Deleted A

Sep 30, 2016

I read some of the other reviews and feel I should comment on some of their criticisms.

The material, objectives and tuition are top-notch. Yes there are things that are unclear and difficult and I you will need to read around the subjects introduced from other sources and persevere.

But that is how you will learn and remember.

So far I have yet to complete the course, I am about to start my 4th attempt, but I get a little further each time and the next presentation acts as revision initially. Daniel Eggar introduces key concepts that you need to master, this course is not spoon fed, but is better for it.

If I have a criticism, perhaps the course is badly named, maybe it should be called "Core statistical concepts for data science using Excel"

By Patrick W

Oct 14, 2020

The course was excellent. A little difficult and overwhelming at times but as long as you stayed the course the professors gave you every opportunity to succeed. Thank you for your time professor.


Dec 20, 2016

Overall, the course material is good with many example. Need a general knowledge with mathematical and statistical from the beginning to pass the exam, because course slide is a little bit fast.

By Yinghuai L

Jul 22, 2020

From ROC to Regression, the course is very carefully and smartly designed, step by step, progress and achievement made with interested topic! the discussion forum is also very useful.

By Mathilde S

Jan 2, 2021

NOT beginners level and errors in material

By lu z

Dec 23, 2020

The name of this course is excel,but from week2 to the final week, you almost can not see excel any more.All things are related to maths or statistics.At first, I think it is a practical course, but finally I find that it is totally not.Frankly speaking, I am very disappointed .In the end , do not waste time and money on this course.You deserve something better.

By Roger L

Jul 28, 2021

The course title is misleading, at-least to me. I consider myself decent with Excel Data Manipulation, and hence would not have selected this course to learn. But stumbled upon this course by chance.

To my pleasant surprise, this course exposes you to model development for a credit-card company. You will have to work on sample data and come up with a simple statistical model to maximize the profit for credit-card underwriting.

These days, even though you can use machine learning software package like Scikit Learn to automate all these steps for model evaluation, as a practitioner it is important to know the mechanics behind it, and the best way to learn is through practice.

The assignment is difficult and it's difficult for a reason. Good things don't come easily.

By Luke C

Jun 7, 2021

Very useful course! The focus on the statistics required for big data analysis was a bit daunting at first, but very much worth it once you're able to complete the meaningful final exam. I'd recommend new students to stick it out through the very technical middle section of the course as it all makes sense later on.

By Hardik M

Mar 4, 2019

The course is great as it allows you to apply all the concepts taught in scenarios that are really practical. The resources supplied with the course are extremely useful,and all in all the course is good for anyone trying to understand data analytics.

By Marek Z

Dec 24, 2015

For me a great course that tackle basics of data analysis that is usually done in much more advanced software.

Thanks to Excel "transparency" it is very easy to understand those concepts.

By Achmad R A

May 21, 2019

its a good course but maybe in the future you can add another case for participants to build another model beside bank credit model

By Soukaina K

May 2, 2019

Excellent course, I learnt a lot and really enjoyed it. Definitely recommend !

By valentine M

Apr 12, 2019

Great course improves data analysis insight

By Eddie M

Nov 16, 2018

The course is quite challenging and therefore worth doing. The materials provided are excellent and the video tutorials and Professor are excellent - but make sure you pay attention!

However, I was a bit disappointed with some of the quizzes particularly those in the final project. The penultimate quiz and peer assignment quiz do have problems. The penultimate quiz answers are not accurate and do not match the actual correct answers. You therefore need to be careful when responding and choose the answer that is closest to your result. On the peer review problem setting there are certain aspects required in your answer that are not defined in the problem. Indeed the way the problem is set out it appears that you can choose between predictive linear regression OR binary classification. Beware.

Also I would strongly recommend finishing the course work for week 3 AND 4 BEFORE taking the quiz on probability and distributions.

By Kenneth W

Oct 11, 2018

Great course. My one caveat would be that, as other reviews have stated, the name of the course is misleading. In my opinion, this course isn't nearly about Excel as much as it is about probability and statistical analysis. If you haven't taken classes and don't have any experience with these, you will be in for a very rough ride. However, Professor Eggers does a good job of guiding you through it and gives you the resources you need to succeed. It will undoubtedly be tough, but if you are persistent and believe in yourself, you will succeed. And you will come out on the other side better for the wear. Cheers!

By Doug J

Apr 29, 2019

Very comprehensive. Lot of theory and practical. My request would be to add a week focusing on a couple models and a couple methods to select metrics and validate confidence.

By Santiago H

Jun 30, 2019

The exercises, resources and quizzes were really good. I felt they were putting to you to the test to see if you had applicable Excel knowledge.

The videos I believe were not that helpful. Too focused on the arithmetics of statistics, while lacking a stronger explanation behind the logic and the importance of certain concepts such as conditional probability, CLT, etc. The arithmetics you will i) forget ii) can easily look them up. But the logic not so much.

I do think the course should have shown how to run regressions with the Data Add-In. This is a helpful tool, makes more sense than forcing you to do everything manually.

By Ethan h

Dec 13, 2020

Sloppy. There's a lot of good material in there, and well presented in general, but the quizzes and assignments are just plain sloppy. It's painfully obvious from grading peers that most people don't get the material at all, which isn't surprising. But I don't like being put in the position of having to peer review people when they don't seem to have put the effort into learning this material on their own, where the assignments didn't make it clear to them. The forums are basically ghost towns. This should be a free course, not paid. If you want to charge people for this, clean it up please.

By Matthew T

Apr 30, 2019

There were a lot of holes in the teaching of this class. We covered more statistics content than I did in my full-time MBA statistics class over a few 10 minute YouTube videos. Additionally, there is some calculus which I have not studied in 10 years or so. I would have liked to see more excel functionalities explained to add to my tool bag. With all that being said, I learned from the class and enjoyed some of the spreadsheets that were provided. I expected to be challenged since the course is done through a prestigious university and definitely was.

By Christopher A

Mar 18, 2020

The material ramped up in difficulty very quickly. It was a miracle that I completed the final project after initially giving up hope. There were no examples in Excel for how to do many of the stat problems despite the course being about excel. If it was not for the Discussion forums I would not have passed the class. I was lost frequently. That being said though I did learn a lot, but since the explanations are sparse, I am not sure if I will retain this or how well I can apply it professionally without making a mistake.