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
"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, Dec 12 & 19
Delivery Method: Live Online
Time: 8:30am - 4:30pm CT
Platform: Zoom
Instructor: Corey Fritsch PhD
Fee:
$845 by Nov 28, 2023
$895 after Nov 28, 2023
CEUs: 1.4
Enrollment Limit: 12
Program Number: 5020-15459
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: Dec 12, 2023
Date: 2 Wed, Apr 17 & 24
Delivery Method: In-person
Time: 8:30am - 4:30pm CT
Location: UWM School of Continuing Education
Instructor: Corey Fritsch PhD
Fee:
$845 by Apr 3, 2024
$895 after Apr 3, 2024
CEUs: 1.4
Enrollment Limit: 12
Program Number: 5020-15464
Registration Deadline: Apr 17, 2024
