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Using Predictive Analytics for Business

This course helps you take your knowledge of data and turn it into meaningful insights. Predictive analytics can help you not only understand what your previously collected data show, but what will most likely happen in the future. Learn how to leverage tools to make statistical inferences easy for all people to accomplish and communicate their findings.

This course can be applied to the Data Analysis Certificate.

Instructor

Corey  Fritsch, MS

Corey Fritsch, MS

Corey Fritsch is an experienced data analyst with a passion for continued learning and research. Fritsch is currently pursuing his Doctor of Philosophy in Educational Statistics and Measurement at UW-Milwaukee, as well as graduate certificates in Applied Data Analysis and ... read more

Benefits and Learning Outcomes

  1. Understand how predictive analytics can be used to turn data into future information and knowledge
  2. Use appropriate models of analysis based on the situation or collected data
  3. Use predictive analytics to solve business or other problems

Course Outline/Topics

Introduction to predictive analytics

  • Review of descriptive analytics
  • Review of predictive analytics
  • Review of prescriptive analytics
  • Supervised and unsupervised learning
  • Examples of predictive analytics that affect your life
  • Variance
  • Correlation
  • Causation
  • Confidence Intervals

Steps to creating a predictive model

  • Target and dependent variables
  • Predictors and independent variables
  • Sample and population
  • Null hypothesis
  • Collect, gather and manipulate data

Evaluating a predictive model

  • Differences in fields
  • Accuracy
  • Types of error
  • Alpha levels
  • Comparison of results from models
  • Parsimonious models

Supervised learning

  • Linear regression
  • Logistic regression
  • Forecasting

Unsupervised learning

  • Clustering
  • Association

Prerequisites

It is highly recommended that participants have taken the Data Foundations course or have equivalent experience in data analysis.  It is also very helpful to have taken Python or have experience in Python or R prior to this course.

Testimonials

"Great course. The hands-on activities were well managed. Only recommendation is more and shorter hands-on activities.

Nice job young man. I enjoyed being a part of the course. Corey is able to present complex data theories and make them applicable to everyday needs. I appreciated his efforts both personally and professionally. Thank you for making this course available.

Again thank you for offering such a great hands-on course. It was a pleasure to be a part of."  —  Participant, April 2021

"Corey is a great instructor and took the time to make sure we understood the content.

I love the online format. I’m trying to finish all the courses before in-person class starts up again because it is more cost-efficient and time-saving."  —  Participant, April 2021

"Corey should teach all the classes."  —  Participant, April 2021

"Great class and excellent instructor!"  —  Participant, April 2019

"I felt the hands-on experience was a great way to apply the knowledge to my own work."  —  Participant, April 2019

"Corey is a great teacher. He adapts well to the group and the questions asked. He is able to alter content to suit the group."  —  Participant, Fall 2018

Date: 2 Tue, Nov 2-9

Delivery Method: Live Online

Time: 8:30am-4:30pm CT

Platform: Zoom

Instructor: Corey Fritsch MS

Fee:

$845 by Oct 19
$895 after Oct 19

CEUs: 1.4

Enrollment Limit: 20

Program Number: 5020-13897

Note: Participants will receive instructions for logging into Canvas to access course materials and Zoom links prior to the first day of class.

Registration Deadline: Nov 2

Register Now

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