课程信息
4.2
2,696 个评分
608 个审阅
专项课程
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
完成时间(小时)

完成时间大约为27 小时

建议:6 weeks, 8-10 hours per week...
可选语言

英语(English)

字幕:英语(English)

您将获得的技能

Binary ClassificationData AnalysisMicrosoft ExcelLinear Regression
专项课程
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
完成时间(小时)

完成时间大约为27 小时

建议:6 weeks, 8-10 hours per week...
可选语言

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 1 小时

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 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, and all assignments are designed to be done in MS Excel. 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 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. ...
Reading
2 个视频 (总计 11 分钟), 2 个阅读材料
Video2 个视频
Introduction to Mastering Data Analysis in Excel6分钟
Reading2 个阅读材料
Specialization Overview10分钟
Course Overview10分钟
完成时间(小时)
完成时间为 2 小时

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 Excel spreadsheets that accompany later videos in this course. ...
Reading
8 个视频 (总计 52 分钟), 1 个阅读材料, 2 个测验
Video8 个视频
Basic Excel Vocabulary; Intro to Charting7分钟
Arithmetic in Excel2分钟
Functions on Individual Cells3分钟
Functions on a Set of Numbers10分钟
Functions on Ordered Pairs of Data8分钟
Sorting Data in Excel5分钟
Introduction to the Solver Plug-in8分钟
Reading1 个阅读材料
Tips for Success10分钟
Quiz2 个练习
Excel Essentials Practice30分钟
Excel Essentials30分钟
2
完成时间(小时)
完成时间为 2 小时

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 measures for comparing and optimizing the performance of the algorithms used to classify collections into two groups. You will learn how and why to apply these different metrics, including how to calculate the all-important AUC: the area under the Receiver Operating Characteristic (ROC) Curve. ...
Reading
6 个视频 (总计 46 分钟), 1 个阅读材料, 2 个测验
Video6 个视频
Bombers and Seagulls: Confusion Matrix8分钟
Costs Determine Optimal Threshold4分钟
Calculating Positive and Negative Predictive Values5分钟
How to Calculate the Area Under the ROC Curve11分钟
Binary Classification with More than One Input Variable7分钟
Reading1 个阅读材料
Tips for Success10分钟
Quiz2 个练习
Binary Classification (practice)30分钟
Binary Classification (graded)45分钟
3
完成时间(小时)
完成时间为 2 小时

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 aggregate uncertainty of all possible outcomes. The entropy measure provides the framework for accountability in data-analytic work. Entropy gives you the power to quantify the uncertainty of future outcomes relevant to your business twice: using the best-available estimates before you begin a project, and then again after you have built a predictive model. The difference between the two measures is the Information Gain contributed by your work....
Reading
7 个视频 (总计 42 分钟), 1 个阅读材料, 2 个测验
Video7 个视频
Probability and Entropy7分钟
Entropy of a Guessing Game7分钟
Dependence and Mutual Information3分钟
The Monty Hall Problem8分钟
Learning from One Coin Toss, Part 15分钟
Learning From One Coin Toss, Part 28分钟
Reading1 个阅读材料
Tips for Success10分钟
Quiz2 个练习
Using the Information Gain Calculator Spreadsheet (practice)30分钟
Information Measures (graded)45分钟
4
完成时间(小时)
完成时间为 3 小时

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 estimate” plus a “confidence interval,” or converted into an information gain measure. You will develop a fluent knowledge of these concepts and the many valuable uses to which linear regression is put in business data analysis. This module also teaches how to use the Central Limit Theorem (CLT) to solve practical problems. The two topics are closely related because regression and the CLT both make use of a special family of probability distributions called “Gaussians.” You will learn everything you need to know to work with Gaussians in these and other contexts. ...
Reading
11 个视频 (总计 73 分钟), 1 个阅读材料, 3 个测验
Video11 个视频
Introduction to Standardization4分钟
Standard Normal Probability Distribution in Excel7分钟
Calculating Probabilities from Z-scores4分钟
Central Limit Theorem3分钟
Algebra with Gaussians6分钟
Markowitz Portfolio Optimization12分钟
Standardizing x and y Coordinates for Linear Regression6分钟
Standardization Simplifies Linear Regression9分钟
Modeling Error in Linear Regression10分钟
Information Gain from Linear Regression5分钟
Reading1 个阅读材料
Tips for Success10分钟
Quiz3 个练习
The Gaussian (practice)30分钟
Regression Models and PIG (practice)45分钟
Parametric Models for Regression (graded)45分钟
4.2
608 个审阅Chevron Right
职业方向

32%

完成这些课程后已开始新的职业生涯
工作福利

25%

通过此课程获得实实在在的工作福利

热门审阅

创建者 JEOct 31st 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.

创建者 NCDec 20th 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.

讲师

Avatar

Jana Schaich Borg

Assistant Research Professor
Social Science Research Institute
Avatar

Daniel Egger

Executive in Residence and Director, Center for Quantitative Modeling
Pratt School of Engineering, Duke University

关于 Duke University

Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world....

关于 Excel to MySQL: Analytic Techniques for Business 专项课程

Formulate data questions, explore and visualize large datasets, and inform strategic decisions. In this Specialization, you’ll learn to frame business challenges as data questions. You’ll use powerful tools and methods such as Excel, Tableau, and MySQL to analyze data, create forecasts and models, design visualizations, and communicate your insights. In the final Capstone Project, you’ll apply your skills to explore and justify improvements to a real-world business process. The Capstone Project focuses on optimizing revenues from residential property, and Airbnb, our Capstone’s official Sponsor, provided input on the project design. Airbnb is the world’s largest marketplace connecting property-owner hosts with travelers to facilitate short-term rental transactions. The top 10 Capstone completers each year will have the opportunity to present their work directly to senior data scientists at Airbnb live for feedback and discussion....
Excel to MySQL: Analytic Techniques for Business

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