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Opiniones y comentarios de aprendices correspondientes a Mastering Data Analysis in Excel por parte de Universidad Duke

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732 revisiones

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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....

Principales revisiones


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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326 - 350 de 715 revisiones para Mastering Data Analysis in Excel

por Jagmohan M

Dec 28, 2018

Great !

por Liu Y

Oct 29, 2017

like it

por Cristian D A

Dec 13, 2015


por Pramit A M

Nov 02, 2015


por Jose C S M

Feb 11, 2016


por Marica C

Dec 13, 2015



Dec 02, 2015


por Dishant P

Feb 12, 2020


por Chirag K

Sep 27, 2019


por Meenal C

Dec 05, 2018


por Bharath M

Jul 04, 2017


por Кирилл

Apr 07, 2017


por Kyle A

Feb 22, 2016


por Malgorzata P

Feb 10, 2016


por Michal K

Oct 07, 2017


por winnielou

Oct 24, 2016


por Al S

Dec 17, 2015


por Tania K

Dec 08, 2015


por 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.

por Max H

Dec 14, 2015

Entering this course with a pretty in-depth knowledge of Excel, it was good to be able to brush up on some things I don't use on a day-to-day 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 double-check 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 follow-along with.

por Charlie C

Jul 10, 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 out-of-scope 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.

por Rebecca S

Mar 27, 2018

I learned a ton, but the course was TOUGH! You really have to hunker down, pay close attention, and take notes...sometimes even re-watch 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.

por Sonya G

Jan 16, 2016

Quite an useful course for Excel application in business decision-making. 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 :(

por Alfredo Z

Feb 20, 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.

por Oleksandr Z

Mar 04, 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).