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 following certificates:
AI Python Certificate
Data Analysis – Advanced Certificate
Data Analysis Certificate
Instructor
Corey Fritsch is an experienced data analyst with a passion for continued learning and research. Fritsch earned his Doctor of Philosophy in educational statistics and measurement at UW-Milwaukee, as well as graduate certificates in applied data analysis and business analytics. ... read more
Benefits and Learning Outcomes
- Understand how predictive analytics can be used to turn data into future information and knowledge
- Use appropriate models of analysis based on the situation or collected data
- 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
"I truly enjoyed Corey as an instructor for this course, and with the in-person format. He never made me (or anyone else) feel foolish for asking questions and encouraged the engagement. He was able to modify the content to be understandable and brought examples that made it more interesting and digestible for me. I will absolutely take all of his classes. Having done an asynchronous and in-person course with him, I hope that the next course with him will be in-person as he shines in this format." — Leila Sadoughian, Milwaukee Public Schools, Spring 2024
"Corey encourages a real interactive classes and there is a lot of student engagement which makes it interesting. Great class for understanding use cases of predictive analytics in real world/ work problems" — Jose George, Stella and Chewys, Spring 2024
"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, Apr 8-15, 2025
Delivery Method: In-person
Time: 8:30am-4:30pm CT
Location: UWM School of Continuing Education
Instructor: Corey Fritsch PhD
Fee:
$845 by Mar 25, 2025
$895 after Mar 25, 2025
CEUs: 1.4
Enrollment Limit: 20
Program Number: 5020-16583
Registration Deadline: Apr 7, 2025
