What you will learn from the Mastering Data Analysis in Excel
- Design and implement realistic predictive models based on data
- 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.
- Excel vocabulary and functions
- Functions on Individual Cells
- Functions on a Set of Numbers
- Functions on Ordered Pairs of Data
- Sorting Data in Excel
- Calculating Positive and Negative Predictive Values
- How to Calculate the Area Under the ROC Curve
- How to calculate and apply entropy
- Standard Normal Probability Distribution in Excel
- Standardizing x and y Coordinates for Linear Regression
- How to apply linear regression models when your input consists of multiple types of data for each event
- Understanding Why Over-fitting Happens
Course Instructor: Jana Schaich Borg, Daniel Egger & Offered by Duke University from Coursera
Course Duration: 21 hours to complete
Course is for Beginner Level
Can I download Mastering Data Analysis in Excel course?
You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The Mastering Data Analysis in Excel course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.Are there any other coupons available for this course?
You can check out for more Udemy coupons @ www.coursecouponclub.com
Note: 100% OFF Udemy coupon codes are valid for maximum 3 days only. Look for "ENROLL NOW" button at the end of the post.
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Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
