Chevron Left
Introduction to Predictive Modeling(으)로 돌아가기

미네소타 대학교의 Introduction to Predictive Modeling 학습자 리뷰 및 피드백

61개의 평가

강좌 소개

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)....

최상위 리뷰


2021년 9월 17일

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.


2021년 10월 15일

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 !

필터링 기준:

Introduction to Predictive Modeling의 16개 리뷰 중 1~16

교육 기관: Adam n

2021년 5월 16일

교육 기관: CHIN W L

2021년 5월 14일

교육 기관: J H

2021년 5월 30일

교육 기관: Kevin D

2021년 7월 30일

교육 기관: Chananthorn S

2021년 9월 9일

교육 기관: Noaman R

2021년 9월 18일

교육 기관: Kima

2021년 10월 16일

교육 기관: Madeline A

2022년 10월 6일

교육 기관: Chris N

2022년 1월 25일

교육 기관: Ngoc T D T

2022년 11월 25일

교육 기관: Komal B

2022년 2월 16일

교육 기관: Jehangeer

2022년 11월 1일

교육 기관: Khubaib K

2021년 9월 10일

교육 기관: Nazar K

2022년 4월 17일

교육 기관: Vishwanath S

2022년 8월 22일

교육 기관: Michael O

2022년 5월 25일