Mastering Data Analysis in Excel

Name: Mastering Data Analysis in Excel
Rating: 5.0 (1 reviews)
Author: Duke University

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课程

英语

60 时

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来自www.coursera.org

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6 序列
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课程详情

教学大纲

Week 1 - About This Course
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 appli...
Week 1 - Excel Essentials for Beginners
In this module, will explore the essential Excel skills to address typical business situations you may encounter in the future. The Excel vocabulary and functions taught throughout this module make it possible for you to understand the additional explanatory E...
Week 2 - Binary Classification
Separating collections into two categories, such as “buy this stock, don’t but that stock” or “target this customer with a special offer, but not that one” is the ultimate goal of most business data-analysis projects. There is a specialized vocabulary of measu...
Week 3 - Information Measures
In this module, you will learn how to calculate and apply the vitally useful uncertainty metric known as “entropy.” In contrast to the more familiar “probability” that represents the uncertainty that a single outcome will occur, “entropy” quantifies the aggreg...
Week 4 - Linear Regression
The Linear Correlation measure is a much richer metric for evaluating associations than is commonly realized. You can use it to quantify how much a linear model reduces uncertainty. When used to forecast future outcomes, it can be converted into a “point esti...
Week 5 - Additional Skills for Model Building
This module gives you additional valuable concepts and skills related to building high-quality models. As you know, a “model” is a description of a process applied to available data (inputs) that produces an estimate of a future and as yet unknown outcome as ...
Week 6 - Final Course Project
The final course project is a comprehensive assessment covering all of the course material, and consists of four quizzes and a peer review assignment. For quiz one and quiz two, there are learning points that explain components of the quiz. These learning po...