Chevron Left
Back to Introduction to Predictive Modeling

Learner Reviews & Feedback for Introduction to Predictive Modeling by University of Minnesota

4.8
stars
62 ratings

About the Course

Welcome to Introduction to Predictive Modeling, the first course in the University of Minnesota’s Analytics for Decision Making specialization. This course will introduce to you the concepts, processes, and applications of predictive modeling, with a focus on linear regression and time series forecasting models and their practical use in Microsoft Excel. By the end of the course, you will be able to: - Understand the concepts, processes, and applications of predictive modeling. - Understand the structure of and intuition behind linear regression models. - Be able to fit simple and multiple linear regression models to data, interpret the results, evaluate the goodness of fit, and use fitted models to make predictions. - Understand the problem of overfitting and underfitting and be able to conduct simple model selection. - Understand the concepts, processes, and applications of time series forecasting as a special type of predictive modeling. - Be able to fit several time-series-forecasting models (e.g., exponential smoothing and Holt-Winter’s method) in Excel, evaluate the goodness of fit, and use fitted models to make forecasts. - Understand different types of data and how they may be used in predictive models. - Use Excel to prepare data for predictive modeling, including exploring data patterns, transforming data, and dealing with missing values. This is an introductory course to predictive modeling. The course provides a combination of conceptual and hands-on learning. During the course, we will provide you opportunities to practice predictive modeling techniques on real-world datasets using Excel. To succeed in this course, you should know basic math (the concept of functions, variables, and basic math notations such as summation and indices) and basic statistics (correlation, sample mean, standard deviation, and variance). This course does not require a background in programming, but you should be familiar with basic Excel operations (e.g., basic formulas and charting). For the best experience, you should have a recent version of Microsoft Excel installed on your computer (e.g., Excel 2013, 2016, 2019, or Office 365)....

Top reviews

NR

Sep 17, 2021

Loved the forecasting lecture. I've used other forecasting methods but learned the composite method first time. Highly recommended course for supply chain and manufacturing students and professionals.

AK

Oct 15, 2021

This course is amazing. very well structured and logical teaching sequence and explaination. I've learned through this course more than the lectures from my university. thanks a lot !

Filter by:

1 - 16 of 16 Reviews for Introduction to Predictive Modeling

By Adam n

May 16, 2021

By CHIN W L

May 14, 2021

By J H

May 30, 2021

By Kevin D

Jul 30, 2021

By Chananthorn S

Sep 9, 2021

By Noaman R

Sep 18, 2021

By Kima

Oct 16, 2021

By Madeline A

Oct 6, 2022

By Chris N

Jan 25, 2022

By dung t

Nov 25, 2022

By Komal B

Feb 16, 2022

By Jehangeer

Nov 1, 2022

By Khubaib K

Sep 10, 2021

By Nazar K

Apr 17, 2022

By Vishwanath S

Aug 22, 2022

By Michael O

May 25, 2022