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## Mastering Data Analysis in Excel, Duke University

4.2
2,695 ratings
608 reviews

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

By JE

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.

By NC

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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589 Reviews

By Olga Atiukina

Dec 08, 2018

Difficult, but i'm glad to tried and completed. Thanks to all, who created this course.

By Ricardo Cabrita

Dec 08, 2018

Too much theory and no excel learings.

By Dove

Dec 08, 2018

Too much math makes it difficult to comprehend. I like week 1, basic excel also practical and easy to understand. But after week 1 everything becomes super confusing... The frustration is real.

By Dao Thu Ha

Dec 06, 2018

The course is very useful. I can learn how to build an effective binary classification model to support for my decision-making process. All learning materials, especially Excel files used in the course is very detailed, greatly assisting me in understanding what the lecturer talk about and how to calculate in Excel.

By Meenal Chaudhary

Dec 05, 2018

ccol

By Jitesh gupta

Dec 02, 2018

One of the best course that i have ever done. Just make a patience and repeat the lecture if u find any difficulty , every time you realise that you are increasing your capablities or knowledge in Data Analytics sector.I will surely recommmcend this course .

By Zhao Mei

Nov 19, 2018

The course is designed very well and digs deeply into the usage of binary models. It will be great if more contents are offered about the multi-factor regression model.

By Eddie McAlone

Nov 16, 2018

The course is quite challenging and therefore worth doing. The materials provided are excellent and the video tutorials and Professor are excellent - but make sure you pay attention!

However, I was a bit disappointed with some of the quizzes particularly those in the final project. The penultimate quiz and peer assignment quiz do have problems. The penultimate quiz answers are not accurate and do not match the actual correct answers. You therefore need to be careful when responding and choose the answer that is closest to your result. On the peer review problem setting there are certain aspects required in your answer that are not defined in the problem. Indeed the way the problem is set out it appears that you can choose between predictive linear regression OR binary classification. Beware.

Also I would strongly recommend finishing the course work for week 3 AND 4 BEFORE taking the quiz on probability and distributions.

By Houda Ait Idder

Nov 13, 2018

The course is very enjoyable. The mathematics behind is sometimes challenging. But the Final Project makes it all worth it.

By Corey Dunn

Nov 09, 2018

The course is very poorly laid out. You are encouraged to work on your final project each week during each module but you don't learn important key elements to complete the final project until later in the course. I enjoyed what I learned in this class, however, stating there are no math prerequisites is misleading. If we were taught the concepts only in Excel, that would be one thing, but to hand solve these statistics problems by hand it really hurts the learn because the professor is speaking above most everyone's head.