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.
Ce cours fait partie de la Spécialisation De Excel à MySQL: techniques d'analyse pour l'entreprise
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Approx. 21 heures pour terminer
Anglais
Sous-titres : Anglais
Compétences que vous acquerrez
Binary ClassificationData AnalysisMicrosoft ExcelLinear Regression
Résultats de carrière des étudiants
23%
ont commencé une nouvelle carrière après avoir terminé ce cours
21%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 2 sur 5 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Approx. 21 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Université Duke
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.
Programme du cours : ce que vous apprendrez dans ce cours
1 heure pour terminer
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 heure pour terminer
2 vidéos (Total 11 min), 2 lectures
2 lectures
Specialization Overview10 min
Course Overview10 min
2 heures pour terminer
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 heures pour terminer
8 vidéos (Total 52 min), 1 lecture, 2 quiz
8 vidéos
Basic Excel Vocabulary; Intro to Charting7 min
Arithmetic in Excel2 min
Functions on Individual Cells3 min
Functions on a Set of Numbers10 min
Functions on Ordered Pairs of Data8 min
Sorting Data in Excel5 min
Introduction to the Solver Plug-in8 min
1 lecture
Tips for Success10 min
2 exercices pour s'entraîner
Excel Essentials Practice30 min
Excel Essentials30 min
2 heures pour terminer
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 heures pour terminer
6 vidéos (Total 46 min), 1 lecture, 2 quiz
6 vidéos
Bombers and Seagulls: Confusion Matrix8 min
Costs Determine Optimal Threshold4 min
Calculating Positive and Negative Predictive Values5 min
How to Calculate the Area Under the ROC Curve11 min
Binary Classification with More than One Input Variable7 min
1 lecture
Tips for Success10 min
2 exercices pour s'entraîner
Binary Classification (practice)30 min
Binary Classification (graded)45 min
2 heures pour terminer
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 heures pour terminer
7 vidéos (Total 42 min), 1 lecture, 2 quiz
7 vidéos
Probability and Entropy7 min
Entropy of a Guessing Game7 min
Dependence and Mutual Information3 min
The Monty Hall Problem8 min
Learning from One Coin Toss, Part 15 min
Learning From One Coin Toss, Part 28 min
1 lecture
Tips for Success10 min
2 exercices pour s'entraîner
Using the Information Gain Calculator Spreadsheet (practice)30 min
Information Measures (graded)45 min
3 heures pour terminer
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 heures pour terminer
11 vidéos (Total 73 min), 1 lecture, 3 quiz
11 vidéos
Introduction to Standardization4 min
Standard Normal Probability Distribution in Excel7 min
Calculating Probabilities from Z-scores4 min
Central Limit Theorem3 min
Algebra with Gaussians6 min
Markowitz Portfolio Optimization12 min
Standardizing x and y Coordinates for Linear Regression6 min
Standardization Simplifies Linear Regression9 min
Modeling Error in Linear Regression10 min
Information Gain from Linear Regression5 min
1 lecture
Tips for Success10 min
3 exercices pour s'entraîner
The Gaussian (practice)30 min
Regression Models and PIG (practice)45 min
Parametric Models for Regression (graded)45 min
Avis
Meilleurs avis pour MASTERING DATA ANALYSIS IN EXCEL
par JE30 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.
par MC27 févr. 2016
Highly useful and practical course. it can be a bit challenging for Uni graduate from irrelevant field. the First course and the visualisation course from this series of specialisation is okay .
par NC19 déc. 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.
par JL14 avr. 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.
À propos du Spécialisation De Excel à MySQL: techniques d'analyse pour l'entreprise
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.
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
Quelle est la politique de remboursement ?
Si vous vous abonnez, vous bénéficiez d'une période d'essai gratuite de 7 jours, durant laquelle vous pouvez annuler votre abonnement sans pénalité. Ensuite, nous n'accordons plus de remboursements, mais vous pouvez annuler votre abonnement à tout instant. Consultez notre politique de remboursement complète.
Une aide financière est-elle possible ?
Oui, Coursera offre une Aide Financière aux étudiants qui n'ont pas les moyens d'acquitter les frais. Demandez-la en cliquant sur le lien Aide Financière sous le bouton S'inscrire situé à gauche. Vous devrez remplir un formulaire de demande et vous serez averti(e) si elle est acceptée. Vous devrez répéter cette procédure pour chaque cours de la Spécialisation, y compris pour le Projet Final. En savoir plus.
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.
D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.
