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Avis et commentaires pour d'étudiants pour Mastering Data Analysis in Excel par Université Duke

3,457 évaluations
809 avis

À propos du cours

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....

Meilleurs avis


Oct 31, 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.


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.

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351 - 375 sur 788 Avis pour Mastering Data Analysis in Excel

par Franco A M A

Jan 11, 2016


par Monica C M

Dec 27, 2015


par Hector G

Sep 05, 2020


par AshQiu

Nov 28, 2019



Oct 30, 2019


par Jagmohan M

Dec 28, 2018

Great !

par Liu Y

Oct 29, 2017

like it

par Cristian D A

Dec 13, 2015


par Pramit A M

Nov 02, 2015


par Jose C S M

Feb 11, 2016


par Marica C

Dec 13, 2015



Dec 02, 2015


par Dishant P

Feb 12, 2020


par Chirag K

Sep 27, 2019


par Meenal C

Dec 05, 2018


par Bharath M

Jul 04, 2017


par Кирилл

Apr 07, 2017


par Kyle A

Feb 22, 2016


par Malgorzata P

Feb 10, 2016


par Michal K

Oct 07, 2017


par winnielou

Oct 24, 2016


par Al S

Dec 17, 2015


par Tania K

Dec 08, 2015


par Isa P

Jun 04, 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 real-world 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 post-quiz materials persisted through weeks 3-6 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

Sep 17, 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