Chevron Left
Вернуться к Introduction to Predictive Modeling

Отзывы учащихся о курсе Introduction to Predictive Modeling от партнера Миннесотский университет

4.8
звезд
Оценки: 62

О курсе

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)....

Лучшие рецензии

NR

17 сент. 2021 г.

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

15 окт. 2021 г.

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 !

Фильтр по:

1–16 из 16 отзывов о курсе Introduction to Predictive Modeling

автор: Adam n

•

16 мая 2021 г.

автор: CHIN W L

•

14 мая 2021 г.

автор: J H

•

30 мая 2021 г.

автор: Kevin D

•

30 июля 2021 г.

автор: Chananthorn S

•

9 сент. 2021 г.

автор: Noaman R

•

18 сент. 2021 г.

автор: Kima

•

16 окт. 2021 г.

автор: Madeline A

•

6 окт. 2022 г.

автор: Chris N

•

25 янв. 2022 г.

автор: dung t

•

25 нояб. 2022 г.

автор: Komal B

•

16 февр. 2022 г.

автор: Jehangeer

•

1 нояб. 2022 г.

автор: Khubaib K

•

10 сент. 2021 г.

автор: Nazar K

•

17 апр. 2022 г.

автор: Vishwanath S

•

22 авг. 2022 г.

автор: Michael O

•

25 мая 2022 г.

Coursera Footer

Начните карьеру или продвиньтесь по карьерной лестнице

Смотреть популярные темы

Популярные курсы и статьи

Получите диплом или сертификат онлайн

Coursera

Сообщество

Еще

Учитесь, где угодно
Placeholder
Placeholder
Placeholder