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

4.2
stars
3,874 ratings

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 youâ€™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

TB

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

JE

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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451 - 475 of 923 Reviews for Mastering Data Analysis in Excel

By Chen H Y

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Feb 22, 2021

The course material itself may not be so easy for people with no background knowledge. On discussion forum, classmates are much more helpful than mentors. About final project: (a) the questions asked in the final project didn't clarify what metrics to display, only to describe the grading criteria in peer-grading session. (b) more tips could have been given to classifying applicants. If we can have more opportunities to practice, it will be even better.

By Oleksandr Z

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Mar 4, 2017

The course is both tough and interesting. The interesting bit comes from developing a model for a credit card company, which is a rather creative and captivating process. The tough part is in hectic learning of a vast array of statistical terms, often poorly explained â€“ and alost never applied to practice (it is true that some of statistical metrics are "applied" in quizzed but it is unclear what's their purpose besides computing yet another number).

By Jianxu S

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Oct 29, 2019

This course teaches the skills and techniques to build and analyze both predictive and classification models in EXCEL. The information theory treatment is unique and helpful to understanding the underlining business objectives and mathematical principles. Make sure you have studied calculus and probability before taking this course. I compare it to an entry level graduate course. Professor Egger is very good at teaching difficult concepts.

By Keep i S #

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Dec 2, 2015

Great course, great professor and great TA in community discussion. Can't give 5 stars as course introduction and content are not really matching. As per introduction anybody can take and learn this course, but indeed it is far from reality. If you don't have good math and statistic background then you better learn them first...

I personally learnt a lot from this course even though could not get the certificate. Thanks everyone.

By Jessica R

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May 13, 2017

Learned a lot, but instructions were often very unclear, especially in the final week. Luckily there were a lot of students who shared their approach of the final project on the discussion board, so it was easier to figure out what we were supposed to be doing. Without this input, I don't think I could have made it through this course. But overall, I felt really challenged and more ready to approach real world problems.

By Marco B

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May 11, 2021

Good course with focus on maths, probability and statistics to be applied in real situations.

The course provides the skills to analyze data and build predictive models to face, quantify and reduce uncertainty. Excel is the tool used for the scope, however the course is not meant to master Excel itself. So, it's fine if you never even used it, while some prerequisites on probability theory are recommended.

By Fil T

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Oct 25, 2017

The math in this course kicked my butt! It was good to be challenged by binary decision analysis. Tons of great spreadsheet resources here. In one of the quizzes, the incorrect data was given and it took me several weeks to find the correct datasheet but after I found it, everything was smooth. The videos all performed correctly.

The lectures did not exactly correlate to the quizzes, but it was enough.

By Prateek K J

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Dec 23, 2021

The whole course was absolutely amazing and insightful. Gave me so much knowledge on analytics. Highly recommended. Didn't give a 5 star cause sometimes while doing the quizzes, it felt like the knowledge required for some of the questions asked was not taught. Had to figure it out on my own using some other sources. But the instances of that were only a few so overall a really good course.

By Vikas G

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Oct 3, 2019

That's a nice course. It just needs to improve the explanation a bit, which will help students not lose interest in the course and complete it on time without wasting much of time on unnecessary things.

However, on the bright side, wandering here and there on the discussion forum and figuring out the answers ourself was also one of the best part of this course.

By Piotr M M

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Oct 29, 2016

Difficult as hell.When You complete it You really start understanding this area but I think due to level of difficulty teaching staff should be a little more active.Big difference in difficulty in lessons(which are easy)and test(which are sometimes incredibly difficult).If You want to work in Big Data field You HAVE TO complete this course but...expect hell.

By Jan C

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Apr 22, 2020

Very useful course - during the course, I struggled a bit to be sure that I would be able to combine all the knowledge and put together into something meaningful in real practice, but the final assignments in week 6 were really great and through the step by step process of building the model I finally got the whole picture. And it is great! thank you!

By Alice M

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Apr 5, 2021

This class was hard. At times, I felt like quitting, but I'm glad I didn't give up. Some assignments could use more clarity, and some videos need to be broken up. The videos were too dense with terminology, but after hours of searching, slowing down videos, reading discussion forums, and so on, I was able to complete the course. :) Would recommend.

By Will S

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Jan 13, 2016

Amazing volume of topics covered and in a manner that is not overly complicated in terms of testing methodology, but still requires you to do the work. There are still several bugs with the course, test answers and instruction documents on the site, but clearly the course is new so hopefully that will be resolved in coming iterations of the class.

By Jason C D A

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Jan 11, 2016

The course is more on analysis techniques as opposed to Excel shortcuts, tips and tricks. It certainly helps if you have a good background in algebra-level math; if you're looking for a course on how to be an Excel Power User, this might not be the best fit. Otherwise, what I learned here is useful for me. Thanks!

By Chua W T C

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Jun 29, 2016

The course is quite tough for me, but I enjoyed the topics discussed, primary between a binary model and a linear regression model. The addition of Excel into this course adds an application layer, which helps me to bring the concepts to the working world as well, and not just plain academic knowledge.

By Nijat S G

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Jun 21, 2020

The course is very practical and sheds a light on data analyst job, however it may be very sophisticated and has little guidance when it comes to final assignments. A lot of ambiguity is present in final assessment, but it is a very good insight on the scientific background of the data science.

By Jose D P

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Nov 13, 2015

Excelente curso, pero a veces los vÃ­deos o materiales se no son tan expresos en explicaciones y ejercicios para facilitar el entendimiento de lo estudiado. Por ejemplo la semana 2 de matriz de clasificaciÃ³n por su complejidad merecÃ­a mayor detalle en las explicaciones y ejercicios de prÃ¡ctica

By Irina

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Dec 2, 2020

The course is not structured around Excel. Instead Excel is used as a tool for introducing and practicing certain data analysis methods. The assignments were quite interesting and challenging. Overall I found the course beneficial for myself. Though at times a clearer explanation was needed.

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Sep 24, 2019

The course enables me to get the knowledge about binary classification and predictive models I think with these skills I feel well-prepared to excel my skills in Data Science. The tutor explained all mentioned issues clearly however the assignment and quizzes may be written clearly.

By Dali S

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Mar 7, 2018

Excellent course. I am a finance professional with limited statistics knowledge. Was able to follow the lectures. The reason for the 4 stars only is that the quizzes can be confusing with missing or misplaced information. Sometimes you have to search in the forums for hints.

By sudhanshu r

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Jun 27, 2020

The course content was really nice. A few corrections in assignments is required but overall the learning experience was great. The best part is the course does not spoon feeds you everything, you need to put in efforts to complete it which is really important for learning.

By William S

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Apr 6, 2021

very good course, it is too long to me (6 weeks). would be better 4 and not to take some materials. It seems to be a lack of order in the course development but still a good course. Please do not take it if you are not familiar with some basic statistics and probability.

By Colin M

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Mar 24, 2017

Good course, bit disjointed at times and some of the maths is rushed through, or not really relevant. Not sure I need proofs on why standardising figures results in easier to use data, maybe just show us how to do the analysis and apply it to more examples in real life.

By Ka L C

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Feb 17, 2020

I have learnt a lot about creating models with training data set and testing the strength of the model on test data sets. Every quiz is designed brilliantly. The only problem is that questions in the peer-reviewed assignment are not very clear and need some fix.

By YEVGENIY V K

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Feb 2, 2016

Lots of good information. However, this course could be structured a lit bit better. More examples and small practice exercises within the lectures would significantly improve the retention of material.

You should posses at least basic knowledge of statistics.