Duke University - Mastering Data Analysis in Excel
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Mastering Data Analysis in Excel at Coursera Overview
Duration | 21 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Mastering Data Analysis in Excel at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 2 of 5 in the Excel to MySQL: Analytic Techniques for Business Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Approx. 21 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Mastering Data Analysis in Excel at Coursera Course details
- 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.
- 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, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. 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 the 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.
Mastering Data Analysis in Excel at Coursera Curriculum
About This Course
About This Specialization
Introduction to Mastering Data Analysis in Excel
Specialization Overview
Course Overview
Introduction to Using Excel in this Course
Basic Excel Vocabulary; Intro to Charting
Arithmetic in Excel
Functions on Individual Cells
Functions on a Set of Numbers
Functions on Ordered Pairs of Data
Sorting Data in Excel
Introduction to the Solver Plug-in
Tips for Success
Excel Essentials Practice
Excel Essentials
Binary Classification
Introduction to Binary Classification
Bombers and Seagulls: Confusion Matrix
Costs Determine Optimal Threshold
Calculating Positive and Negative Predictive Values
How to Calculate the Area Under the ROC Curve
Binary Classification with More than One Input Variable
Tips for Success
Binary Classification (practice)
Binary Classification (graded)
Information Measures
Quantifying the Informational Edge
Probability and Entropy
Entropy of a Guessing Game
Dependence and Mutual Information
The Monty Hall Problem
Learning from One Coin Toss, Part 1
Learning From One Coin Toss, Part 2
Tips for Success
Using the Information Gain Calculator Spreadsheet (practice)
Information Measures (graded)
Linear Regression
Introducing the Gaussian
Introduction to Standardization
Standard Normal Probability Distribution in Excel
Calculating Probabilities from Z-scores
Central Limit Theorem
Algebra with Gaussians
Markowitz Portfolio Optimization
Standardizing x and y Coordinates for Linear Regression
Standardization Simplifies Linear Regression
Modeling Error in Linear Regression
Information Gain from Linear Regression
Tips for Success
The Gaussian (practice)
Regression Models and PIG (practice)
Parametric Models for Regression (graded)
Additional Skills for Model Building
Describing Histograms and Probability Distributions Functions
Some Important and Frequently Encountered PDFs
Linear Regression with More than One Input Variable
Understanding Why Over-fitting Happens
AUC Calculator Explanation and Spreadsheet
Probability, AUC, and Excel Linest Function
Final Course Project
Final Project Information: Part 1
Final Project Information: Part 2
Final Project Information
Summary of Learning Points for Final Project: Quiz 1
Summary of Learning Points for Final Project: Quiz 2
Part 1: Building your Own Binary Classification Model
Part 2: Should the Bank Buy Third-Party Credit Information?
Part 3: Comparing the Information Gain of Alternative Data and Models
Part 4: Modeling Profitability Instead of Default
Mastering Data Analysis in Excel at Coursera Admission Process
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