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.
Этот курс входит в специализацию ''Специализация От Excel до MySQL: способы анализа бизнес-данных'
Mastering Data Analysis in Excel
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Прибл. 29 часа на выполнение
Предполагаемая нагрузка: 6 weeks, 8-10 hours per week
Английский
Субтитры: Английский
Приобретаемые навыки
Binary ClassificationData AnalysisMicrosoft ExcelLinear Regression
Карьерные результаты учащихся
23%
начал новую карьеру, пройдя эти курсы
21%
получил значимые преимущества в карьере благодаря этому курсу
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 2 из 5 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Прибл. 29 часа на выполнение
Предполагаемая нагрузка: 6 weeks, 8-10 hours per week
Английский
Субтитры: Английский
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Университет Дьюка
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.
Программа курса: что вы изучите
1 ч. на завершение
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.
1 ч. на завершение
2 видео ((всего 11 мин.)), 2 материалов для самостоятельного изучения
2 материала для самостоятельного изучения
Specialization Overview10мин
Course Overview10мин
2 ч. на завершение
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.
2 ч. на завершение
8 видео ((всего 52 мин.)), 1 материал для самостоятельного изучения, 2 тестов
8 видео
Basic Excel Vocabulary; Intro to Charting7мин
Arithmetic in Excel2мин
Functions on Individual Cells3мин
Functions on a Set of Numbers10мин
Functions on Ordered Pairs of Data8мин
Sorting Data in Excel5мин
Introduction to the Solver Plug-in8мин
1 материал для самостоятельного изучения
Tips for Success10мин
2 практического упражнения
Excel Essentials Practice30мин
Excel Essentials30мин
2 ч. на завершение
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.
2 ч. на завершение
6 видео ((всего 46 мин.)), 1 материал для самостоятельного изучения, 2 тестов
6 видео
Bombers and Seagulls: Confusion Matrix8мин
Costs Determine Optimal Threshold4мин
Calculating Positive and Negative Predictive Values5мин
How to Calculate the Area Under the ROC Curve11мин
Binary Classification with More than One Input Variable7мин
1 материал для самостоятельного изучения
Tips for Success10мин
2 практического упражнения
Binary Classification (practice)30мин
Binary Classification (graded)45мин
2 ч. на завершение
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.
2 ч. на завершение
7 видео ((всего 42 мин.)), 1 материал для самостоятельного изучения, 2 тестов
7 видео
Probability and Entropy7мин
Entropy of a Guessing Game7мин
Dependence and Mutual Information3мин
The Monty Hall Problem8мин
Learning from One Coin Toss, Part 15мин
Learning From One Coin Toss, Part 28мин
1 материал для самостоятельного изучения
Tips for Success10мин
2 практического упражнения
Using the Information Gain Calculator Spreadsheet (practice)30мин
Information Measures (graded)45мин
3 ч. на завершение
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.
3 ч. на завершение
11 видео ((всего 73 мин.)), 1 материал для самостоятельного изучения, 3 тестов
11 видео
Introduction to Standardization4мин
Standard Normal Probability Distribution in Excel7мин
Calculating Probabilities from Z-scores4мин
Central Limit Theorem3мин
Algebra with Gaussians6мин
Markowitz Portfolio Optimization12мин
Standardizing x and y Coordinates for Linear Regression6мин
Standardization Simplifies Linear Regression9мин
Modeling Error in Linear Regression10мин
Information Gain from Linear Regression5мин
1 материал для самостоятельного изучения
Tips for Success10мин
3 практического упражнения
The Gaussian (practice)30мин
Regression Models and PIG (practice)45мин
Parametric Models for Regression (graded)45мин
Рецензии
Лучшие отзывы о курсе MASTERING DATA ANALYSIS IN EXCEL
от партнера JEOct 30, 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.
от партнера MCFeb 27, 2016
Highly useful and practical course. it can be a bit challenging for Uni graduate from irrelevant field.\n\nthe First course and the visualisation course from this series of specialisation is okay .
от партнера NCDec 19, 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.
от партнера JLApr 14, 2018
This course is worth taking by anyone who needs to have a better understanding of how the most efficient and best decisions in the market place are taken using Data management simply in Excel.
от партнера NPMay 11, 2018
It was a great course and I learned a lot. However, I think the final project could have been more spaced out. In general, I felt like I needed more time at the end to review Excel Modeling.
от партнера MZDec 23, 2015
For me a great course that tackle basics of data analysis that is usually done in much more advanced software.\n\nThanks to Excel "transparency" it is very easy to understand those concepts.
от партнера RCJan 14, 2017
I love this course and the way the material is explained. I plan on taking this course again to improve my understanding of the information because I think it relays very important ideas.
от партнера TRNov 26, 2017
A challenging course that rewards conscientious effort. Heavy on math, both practical and theoretical. Highly recommend comfort with college level statistics before taking this course.
от партнера PLApr 21, 2016
quite a lot techniques to learn. Just wish they could explain more about applications of those techniques, in more details, which however might be hard to get done in 5 weeks though.
от партнера ASFeb 14, 2019
This course has enabled me to think the way a data analyst need to think. This course helps in independent growth and getting know the topics by own research. Loved it ! Thank you !
от партнера KKSep 17, 2017
An in depth deep dive into the mathematical concepts needed to be understood for data analysis tools and techniques. An all round good introduction into the field of data analytics.
от партнера ARDec 12, 2015
Thank you very much, the lesson is very useful to me. in order to understand what the necessity of a function. and the professor clearly explains everything in the right pace.
от партнера DJApr 28, 2019
Very comprehensive. Lot of theory and practical. My request would be to add a week focusing on a couple models and a couple methods to select metrics and validate confidence.
от партнера PDMar 15, 2016
Dr Eggers is a tremendous professor. The course has wit and application along with assignments that are well scaffolded to the learning content. Highly recommend this class.
от партнера BRJan 16, 2017
I very much enjoyed this course. I've been able to apply some of the strategies I learned in the specialization and I look forward to using it as a resource moving forward.
от партнера RCOct 14, 2018
Challenging course, however very useful skills on leveraging Excel for data analysis. I enjoyed the examples as well as the class projects. Good mix of hands on an theory.
от партнера RMNov 10, 2019
Course is good for those who are looking to get skills in business analysis through excel. The final project does not have a proper reviewer or is not evaluated properly.
от партнера SPMar 14, 2016
Very interactive and simple to learn course.\n\nthe video lectures are very clear to understand and worksheets are helpful to gain a better understanding of the topic.
от партнера KHJan 19, 2018
This course was very helpful in refreshing my knowledge of Excel I had previously and including new tips and tricks for working in Excel that I didn't have before.
от партнера ATDec 20, 2015
This course was a great recap in math/statistics that I had totally forgotten about. Things were explained clearly, and the application of concepts was practical
Специализация От Excel до MySQL: способы анализа бизнес-данных: общие сведения
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.
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Will I receive a transcript from Duke University for completing this course?
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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