Informações sobre o curso
4.2
2,698 classificações
609 avaliações
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Prazos flexíveis

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Horas para completar

Aprox. 27 horas para completar

Sugerido: 6 weeks, 8-10 hours per week...
Idiomas disponíveis

Inglês

Legendas: Inglês

Habilidades que você terá

Binary ClassificationData AnalysisMicrosoft ExcelLinear Regression
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Horas para completar

Aprox. 27 horas para completar

Sugerido: 6 weeks, 8-10 hours per week...
Idiomas disponíveis

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
Horas para completar
1 horas para concluir

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 vídeos (total de (Total 11 mín.) min), 2 leituras
Video2 videos
Introduction to Mastering Data Analysis in Excel6min
Reading2 leituras
Specialization Overview10min
Course Overview10min
Horas para completar
2 horas para concluir

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 vídeos (total de (Total 52 mín.) min), 1 leitura, 2 testes
Video8 videos
Basic Excel Vocabulary; Intro to Charting7min
Arithmetic in Excel2min
Functions on Individual Cells3min
Functions on a Set of Numbers10min
Functions on Ordered Pairs of Data8min
Sorting Data in Excel5min
Introduction to the Solver Plug-in8min
Reading1 leituras
Tips for Success10min
Quiz2 exercícios práticos
Excel Essentials Practice30min
Excel Essentials30min
Semana
2
Horas para completar
2 horas para concluir

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 vídeos (total de (Total 46 mín.) min), 1 leitura, 2 testes
Video6 videos
Bombers and Seagulls: Confusion Matrix8min
Costs Determine Optimal Threshold4min
Calculating Positive and Negative Predictive Values5min
How to Calculate the Area Under the ROC Curve11min
Binary Classification with More than One Input Variable7min
Reading1 leituras
Tips for Success10min
Quiz2 exercícios práticos
Binary Classification (practice)30min
Binary Classification (graded)45min
Semana
3
Horas para completar
2 horas para concluir

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 vídeos (total de (Total 42 mín.) min), 1 leitura, 2 testes
Video7 videos
Probability and Entropy7min
Entropy of a Guessing Game7min
Dependence and Mutual Information3min
The Monty Hall Problem8min
Learning from One Coin Toss, Part 15min
Learning From One Coin Toss, Part 28min
Reading1 leituras
Tips for Success10min
Quiz2 exercícios práticos
Using the Information Gain Calculator Spreadsheet (practice)30min
Information Measures (graded)45min
Semana
4
Horas para completar
3 horas para concluir

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 vídeos (total de (Total 73 mín.) min), 1 leitura, 3 testes
Video11 videos
Introduction to Standardization4min
Standard Normal Probability Distribution in Excel7min
Calculating Probabilities from Z-scores4min
Central Limit Theorem3min
Algebra with Gaussians6min
Markowitz Portfolio Optimization12min
Standardizing x and y Coordinates for Linear Regression6min
Standardization Simplifies Linear Regression9min
Modeling Error in Linear Regression10min
Information Gain from Linear Regression5min
Reading1 leituras
Tips for Success10min
Quiz3 exercícios práticos
The Gaussian (practice)30min
Regression Models and PIG (practice)45min
Parametric Models for Regression (graded)45min
4.2
609 avaliaçõesChevron Right
Direcionamento de carreira

32%

comecei uma nova carreira após concluir estes cursos
Benefício de carreira

25%

consegui um benefício significativo de carreira com este curso

Melhores avaliações

por 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.

por 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.

Instrutores

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Jana Schaich Borg

Assistant Research Professor
Social Science Research Institute
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Daniel Egger

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

Sobre 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....

Sobre o Programa de cursos integrados Excel to MySQL: Analytic Techniques for Business

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

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

  • No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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