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

5.0
stars
13 ratings
4 reviews

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

CL
May 13, 2021

Thanks, I enjoyed the course teaching and new knowledge. Looking forward to continue with the next course in this specialization.

JH
May 29, 2021

I really like how there were lots of examples for us to practice on. It helped to reinforce what we were learning

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1 - 4 of 4 Reviews for Introduction to Predictive Modeling

By Adam n

May 16, 2021

Good course! The videos and instruction are very good. I thought the week 4 coursework was substantially more difficult than the prior three weeks, so be prepared for that. Overall, I really enjoyed the class.

By J H

May 30, 2021

I really like how there were lots of examples for us to practice on. It helped to reinforce what we were learning

By CHIN W L

May 14, 2021

Thanks, I enjoyed the course teaching and new knowledge. Looking forward to continue with the next course in this specialization.

By Kevin D

Jul 30, 2021

This is a great course, I think people starting this should get a grasp of basic statistics and working knowledge of excel to make the learning experience much better. However, I think this course is straightforward and the instructor does go over the material very well! Topics on time series forecasting is a bit of a challenge but follow the videos and exercises, you will be fine:)