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

4.2
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3,833 évaluations
•
932 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

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 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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601 - 625 sur 913 Avis pour Mastering Data Analysis in Excel

par Ravi D

•

30 janv. 2016

Learning some great things!

par Jude O

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24 sept. 2018

Very challenging to grasp

par Mmoloki M

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22 nov. 2020

REALY interesting course

par Jyoti K

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7 oct. 2020

Very good course format.

par Eve D

•

20 mai 2020

Very interesting course

par raghav s

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30 déc. 2015

its very helpful course

par Nick P

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19 avr. 2020

few clear explanations

par Vardges Z

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15 déc. 2018

A lot of useful theory

par ZHANG W

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19 févr. 2022

v​ery good course

par Divya M

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13 mai 2020

Excellent course!

par Pranshu J

•

29 nov. 2015

Extremely helpful

par Raja K P

•

6 oct. 2016

Excellent Course

par Deepak S

•

11 juil. 2017

Good course!

par Tan E

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2 févr. 2019

Very useful

par Chuang M

•

6 févr. 2016

Good course

par Angel S

•

5 févr. 2016

Very useful

par SAHANA S R

•

1 avr. 2021

its useful

par Felipe P

•

15 déc. 2015

Excelent!

par Jay K P

•

3 déc. 2015

Awesome!!

par Zewei R

•

7 août 2019

too hard

par Foo J W

•

17 juin 2020

tough!!

par K C

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4 janv. 2016

Love it

par Ansar A K

•

26 juin 2021

good

par 121913901021 g

•

17 déc. 2020

Good

par Zhengfeng Y

•

25 mai 2016

Go

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