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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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51 - 75 of 934 Reviews for Mastering Data Analysis in Excel

By Ashish R

Feb 11, 2021

This is mathematics, probability and statistics, but shown as Excel, which is just a tool!

By Kaela W

Feb 7, 2016

Probably the worst class I have ever taken on Coursera. The teacher asked us to do tons of things without explaining how and used tons of complicated math formulas without explaining what they were, what they did, or when and how to use them. There were also actual incorrect answers in the videos on occasion, so that even if you did do things correctly, you would think you were wrong and be confused, and there were a lot of inconsistencies between the spreadsheets used in the videos and the methods used to solve things compared to the actual spreadsheets given to us, which makes things pretty impossible to learn. If you're more advanced, it may be easier to find and understand the differences between the video and the spreadsheets, but the whole point of this class is that it is for beginners.

By Miranda F

Dec 20, 2020

For a specialization labeled for beginners, I found this course to be very challenging compared to the other courses in the specialization. I expected that this class would cover pivot tables and how to find and interpret regression using Excel. This was not the course. The teacher explained concepts using upper division math, so I struggled to learn the concepts and did not have a teacher who could explain the concepts. The video lessons had very limited information. They assumed you knew the math already. The course would improve if it covered half the material and had exercises and worksheets that demonstrated how to do the equations.

By Benjamin C

Dec 2, 2015

Warning: The lecture videos along will NOT be enough to prepare you for the final assignment! Be prepared to do your own research for the extra study materials. On the forum, many students said they had to drop out during the last week (probably without getting a refund!) because they were completely caught off guard by the huge knowledge gap between lectures and the final assignment. If you are determined to get the specialization certificate, you should definitely start the final assignment as early as possible. Don't wait until the last week or two!!

By Aaron M

Jul 23, 2019

Completely disorganised. You will be tested on material BEFORE you take the lesson teaching it, making you question your ability. The outline they provide for the order you should take the materials is completely wrong. If you want to learn by a guy scribbling quickly and messily with little in depth explanation about the concepts he teaches, go ahead and take this. Otherwise, avoid at all costs. Also, you learn nothing about using excel to perform data analysis, just given templates with no explanation on how they work.

By Kamal G

Jul 13, 2021

The course was hard and not properly explained. They have only taught the concepts and mathematical formulas in videos instead of applying the concepts on Excel. They have provided reading material assuming students would understand on themselves how to apply the concepts on Excel. In the final course project, we were asked to prepare our model on own. However, throughout the course, it was not practiced. Now, how can a student prepare a model on themselves without practicing given that they only know about the theory.

By Dana O

May 29, 2022

Shame on you for wasting people's time and money by calling this an introductory class.

Introductory classes do NOT have disclaimers that you need pre-reqs. Introductory classes do NOT have introductions to exel formulas that do not include how to utilize that formula.

This class is supposed to be abotu Excel, and instead rabbit-holes into tangental probability. It is poorly written, few practical examples are provided, and the instruction is incoherant and sloppy.

By Fabio P

Apr 24, 2020

There is no Excel here but a lot of theoretical and statistical topics that really make the lessons impossible to be understood if you don't have the appropriate background. At a certain stage, if you want to continue, you need to spend a lot of time to catch up trying to find on line what the trainer is talking about.

It is a pity because I used Coursera already and I was happy with their courses, but not in this case

By Robert N

Dec 23, 2015

If I could give it less than 1 star, I would. It wasn't an Excel class, rather it was a targeted business statistics class with only disjointed lectures and no benefit of textbook to actually help you learn. Lots of errors in the lectures and tests, and little to no support from course staff. Stay away! You won't regret it.

By Meagan M

Jun 11, 2021

Finding a model in quiz 1 module 6 is too hard. I have spent hours trying various models, and have read every discussion thread and watched every video related to finding this model. All to no avail. I am unable to complete this course simply because of this one problem.

By Peter C

Apr 27, 2020

I aced the first two weeks. It was recommended that I finish the first quiz of the final module. The information from the first two weeks would be fresh in my mind. I attempted the quiz, and encountered problems I was in no way prepared for.

By Junxi F

Jun 22, 2021

Lectures are lack of education, most of the questions are too hard and have not been explanied well. His homework are not associated with what he teaches, making the test parts extremely annoying and time comsuming.

By Yebin K

Sep 23, 2020

I am pretty sure that there are a lot of people who have problems with this course.

There should be more information and teaching for Test.

It's hard to utilize the things we learn from video for test...

By konstantin k

May 29, 2021

Useless. Poorly presented material and useless project. I would not recommend it at all. You are waisting your time if you enroll.

By Weston A

Feb 22, 2021

lots of mistakes and errors, and videos are not enough to complete all the coursework

By Prasad H

Aug 17, 2016

Though the Course name is Mastering Data Analysis in Excel. This course will take you beyond Excel mastering skills. Quite a Short Course compare to amount of Statistical and Probability concepts you learn. This course covers most of the concepts and models necessary for any Data Analyst & Data Science students and Professionals. This course is quite challenging and at times frustrating and time consuming but in the end you will feel you learnt something what you don't know. It will be worth your effort.If you don't know something what you don't know. Here is the course, it is an accelerated course. You many not master all of them, you will master some, I can assure any future students Professor will give all the information and concepts that you need to master. Even after completing the exam I keep repeating and going back to videos and notes which is really valuable.

By Chí C N

May 3, 2022

This course sharpens my knowledge of Probability Distribution and teaches a new concept of Binary Classification. It shows me how to apply Business Metrics (Course 1 of this specification), Probability Distribution and Binary Classification to Data Analysis. However, be prepared to conduct some research and seek outside material to understand more deeply becasue you may feel confused at some points as some students have complained, especially when you are a newbie in the field of probability distribution. In my opinion, this is not necessarily a drawback of this course becausue when you are left to self-learning and researching, you are also thriving strongly.

By Rod S

Sep 6, 2016

This course isn't for the faint hearted, you need a decent background in statistics, intermediate mathematics and good grounding in excel. All of these are covered well in the course but there's a lot to take in and I can imagine it being quite tough for those not so familiar. That said, the topics, examples and tools provided are exactly those required to build a good foundation in Business Analytics and I imagine, Data Science. Prof. Egger as always, delivers the course with great aplomb and shares his considerable knowledge in a wise but unassuming manner. Highly recommended.

By Ryan V

Dec 29, 2015

I learnt a lot from this course. The first week seemed very straight forward and I was worried the course was a bit too rudimentary. From there it stepped up four or five gears and I had to work hard to reinforce the concepts and apply the concepts.

A really great course for any analyst or anyone seeking the true insight in data. The discussion board is a wealth of knowledge and a good read with tutors posting very plain english easier to understand answers to questions.

By Seshadri G

Jun 28, 2017

I got to learn life skills that are essential for a data analyst. The biggest addition to my knowledge via this course would have to be binary classification and entropy. Although I was familiar with the theory of probability and statistics prior to taking this course, everything was brought into perspective or context in this course. Grateful to Prof. Egger for his enoromous efforts in recording the videos and providing the spreadsheets for our practice and future use.

By Volney P

Jun 25, 2017

This Course is awesome!

It is incredible how some concepts clearly defined and put into practice turn into a a powerful tools for data analysis... like binary classification models, confusion matrix, bayes theorem.

I am really enjoying this course... I highly recommended to everyone... thanks a lot professor Daniel Egger for sharing your knowledge with us, Coursera and Duke University for making this course available...

Hungry for more...

Volney Poulson

By Swetha J

Nov 22, 2015

Very good course. Loved Daniel's teaching. I have a request to make coming from healthcare/ lifesciences background and a starter to analytics it would be very very helpful if Daniel can include basic/ elementary videos on probability and statistics/ Bio-Statistics in this course to enable us to go deeper.

Else a separate course on BioStatistics and probability would be WOW. Looking forward for more courses from Daniel.



By Sanal

Apr 20, 2021

I believe this is a great course for beginners in data science like me. I really loved the content of the course, presented with so many examples and prof Daniel Egger and his team has done a great job. I must admit that I did not understand many of the videos or concepts at first go, I had to do my share of background reading for every week. Once that is done, I guess you can takeaway so much more from these classes.

By Md. H I S

May 28, 2017


Its has so many things to learn; from understanding the data analysis process to building actual models. This course definitely laid the foundation of basic understanding and implementation of making decision thorough data analysis.

I would recommend this course to whoever is interested in learning data analysis or is involved in rational decision making through the data analysis.

By Lucia A I

Oct 12, 2020

I liked the teaching methods and the content. You don't have to be an expert at Excel, but it requires certain experience in data analysis, algebra, and statistics, so you don't get lost when studying the content. I have an engineering's degree, so I'm not an expert in the topic, but I was interested and I feel satisfied with the knowledge I obtained and the challenges in the final project.