TB
16 nov. 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
30 oct. 2015
The course deserves a 5star 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.
par Meenal C
•5 déc. 2018
ccol
par Bharath M
•4 juil. 2017
good
par Кирилл
•7 avr. 2017
Nice
par Kyle A
•22 févr. 2016
Ver
par Malgorzata P
•10 févr. 2016
:)
par ISHAAN S
•27 juil. 2021

par Michal K
•7 oct. 2017
V
par winnielou
•24 oct. 2016
k
par Al S
•16 déc. 2015
e
par Tania K
•8 déc. 2015
.
par Madeline K
•16 mars 2021
This was a good course for anyone looking to learn advanced excel analytics techniques. I learned a lot and the quizzes and final project give sufficient hands on practice to go along with the videos.
The reason I am not giving this course 5 stars is because there were times when the instructor rushes through some of the concepts in the course. I had a hard time following along at times and had to do a lot of reading in the forums to understand how to complete the final project. I would not rate this as a beginner course, these are advanced data analytics techniques requiring using calculus and statistics in excel. There are also some errors in the quizzes and I found that the course mentors are not super active in the forums  many of their posts and tips being from 34 years ago.
All that said, I don't want my review to deter folks from taking this course. I learned a lot and I feel very accomplished that I completed it and I am walking away with a thorough understanding of the topics. I'd still recommend this course to anyone who is willing to put in extra hours outside of the course to do your own research, spend time with the spreadsheets, and use the forums.
par Isa P
•3 juin 2018
This course was a rigorous introduction to using Excel for the specific purpose of solving data analytics problems. The challenges were fun and rewarding for those who love mathematics, applications to realworld data problems, and who are comfortable with wrestling with complex concepts independently. The core components of this course were binary classifications, linear regression, and the supporting mathematical and statistical theorems. While the first two weeks of the course were a very steep learning curve (even for a student with a B.A. in Applied Mathematics), the supplemental explanations after submitting assignments helped the learning process. I wished such structure and explanatory postquiz materials persisted through weeks 36 of the course. This would have made it more rewarding, as I came away wishing I could review my weaker areas.
par Yun Q N
•17 sept. 2020
After completing the course, I'd like to say that the title of the course seems quite misleading as it focuses very much on math and statistical concepts behind some of the commonly used techniques and not so much on using excel to perform data analysis. It's interesting to know the concepts behind, but I have to admit that I struggled with the course as I've not touched advanced maths and statistics since college almost 2 decades ago.
From the peer review assignment, it appears that I'm not the only one struggling with the course. One suggestion to Duke University would be to set up screening of the peer review assignments and single out those that have exceptionally short responses, out of 5 that I reviewed, 2 submissions have only (.) in its response. That surely shouldn't be allowed
par Max H
•13 déc. 2015
Entering this course with a pretty indepth knowledge of Excel, it was good to be able to brush up on some things I don't use on a daytoday basis such as VLOOKUP and STANDARDIZE functions. The subject material is quite good, AOC and Binary Classifications were very interesting to learn about and have tons of applications, particularly in operation optimization problems/cases. One point of suggestion would be to doublecheck and clean up the accompanying Excel files. Some of the material was confusing to follow along with. If you could define cells, arrays, and tables for instance it would make the material much more intuitive to followalong with.
par Evan D
•22 févr. 2021
I learned new things, and each time something clicked I felt like it was a huge achievement. Overall, I found this course very hard. Things build on each other so if you don't get any of the steps along the way, then you can't really move on. I think it is anticipated that you have a deeper knowledge of algebra and other concepts in general than I have. This is supposed to take 6 weeks, and it took me 13 weeks, so basically twice as long. To be fair, I spanned the holiday season as well, but overall it took me much longer to complete things than the outline suggests.
par Charlie C
•10 juil. 2019
The material is actually very good. But the assignments have too many overall flaws, flaws that are not fixed in years. It wasted me a ton of time. A lot of materials are also very "skippy" where the instructor derives something suddenly and does not say if this is derived from a outofscope method or what not. It leaves you hanging and rewatching and thinking and wasting time just because he does not explain "hey don't think about it because it's out of scope and i am just giving you the result and nothing else is going on ". All these said, I love the materials.
par Rebecca S
•27 mars 2018
I learned a ton, but the course was TOUGH! You really have to hunker down, pay close attention, and take notes...sometimes even rewatch lectures more than once. I am glad I took the course. The only reason I didn't give it 5 stars is that the lectures can be tough to follow, and the quizzes and assignments have missing or misplaced information that make it difficult to get to the right answer. It takes some serious patience, reading of the supplemental material, and hints from others on the discussion forums.
par Sonya G
•16 janv. 2016
Quite an useful course for Excel application in business decisionmaking. But I think the final project is a little more difficult than weekly assignments. And only Quiz 1 has some hints about the potential problems we might come across during the quiz. The linear regression part, especially multivariate linear regression, need more explanations how to derive the matrix in Excel. Even though I followed every steps and referred other classmates' discussions, I cannot work out the matrix with Excel. So sad :(
par Erin A B
•20 mars 2022
I found significant portions of the Final Project to be very confusing. Part 1 asked us to basically "guess and check" to find a good model, which doesn't seem particularly efficient or reliable. I spent many more hours on that than should have been necessary (910 hours, then moved on just to make more progress). Overall I learned a lot from this course, and I did find the information to be valuable, but the Project could use another look after seven years and many complaints in the Discussion Forum.
par Alfredo Z
•20 févr. 2016
towards end of the course, specifically linear regression week, a lot of buzzwords are strung together. I wish, the instructor would be a little bit more sparing in their usage together (together is the keyword). Eg "This is the connection between linear regression and mutual information in a parametric model where we have gaussian distributions" I feel that each term in isolation I know what they mean, but when strung together, I am unclear how to process the meaning.
par Chen H Y
•22 févr. 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 peergrading session. (b) more tips could have been given to classifying applicants. If we can have more opportunities to practice, it will be even better.
par Oleksandr Z
•4 mars 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 – 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).
par Jianxu S
•29 oct. 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.
par Keep i S #
•2 déc. 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.
par Jessica R
•13 mai 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.