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).
CL
Thanks, I enjoyed the course teaching and new knowledge. Looking forward to continue with the next course in this specialization.
CN
Great course, good topic material and examples and well taught. Overall it was useful and relevant.
GR
Informative. Really liked the spread sheet examples.
BM
Best course structure, very practical, the professor presents very well and easy to follow. I like the exercises and snap quiz within videos. One of my best course so far on Coursera.
DK
A well planned course on predictive modelling with hands on practice on MS Excel.
NP
Thank you De Liu, I thoroughly enjoyed this predictive modeling hands-on tech course !
VS
Contents presentation is very good.Given 1 star less due to non inclusion of ARIMA models.
JH
I really like how there were lots of examples for us to practice on. It helped to reinforce what we were learning
TB
I really enjoyed how the course was geared towards applying the theory. Very useful practical information and well presented!
KK
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 !
NR
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.
SD
Great course. Easy to follow through. A suggestion would be to make a compilation of all the formulas on a doc for ease.
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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.
Thanks, I enjoyed the course teaching and new knowledge. Looking forward to continue with the next course in this specialization.
I really like how there were lots of examples for us to practice on. It helped to reinforce what we were learning
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:)
It is one of the best compact course in Excel spreadsheet in coursera. It covers several advanced topics in Statistics and Data Analysis by using a lot of advanced techniques in Excel combining with the corresponding literacy.
The main syllabus prepares someone to follow other methods in Machine Learning and Time-series Statistics (like, ARIMA) or Classification Methods, even though to learn these important methods. It was a happy moment to learn about data cleaning and several concepts like Pivot Tables, Interaction Statistics, Seasonal Analysis,... etc.
After this successful attendance, I am very confident to work on Prediction Analysis by using a spreadsheet and being able to explain what happens in different numerical results and graphs. This course applies as a complement unit to a solid background in statistics and mathematics (i.e., series expansion, F-test, etc) for a better understanding of the common stochastic models in Time-series module. It is not a mathematically oriented unit but the mathematics is the basic thinking.
A special note: This course gives a first view of Excel Solver for optimization problems that is important to the course 3 of this specialization.
This course is the basic of business analytic course but not easy for me because my English is not good. Instructor De Liu teach easy to listen ,clearly and very helpfully for choosing accuracy data analytic model with demonstrated examples. I don't good at in English but I can listen and understood the lesson that you can learn 30 minute/day very short and suitable for study among working day.
J'ai trouvé ce module équilibré, une entrée en douceur dans le monde de la modélisation prédictive, mais qui très vite va dans des éléments concrets et d'un niveau plus que correct. J'ai réalisé ce cours dans le cadre de ma thèse (phd Student) en France, plus une curiosité qu'un besoin, mais c'était vraiment très bien. Peut être que la semaine 4 est un peu plus difficile que les autres !
Really enjoyed this course! I'd been introduced to a few of these topics a long while ago, and they never fully made sense in prior attempts. De Liu did a wonderful job of explaining the concepts, what was happening, which model was appropriate, and how it worked. The hands-on examples and exercises really helped with my understanding.
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.
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 !
Best course structure, very practical, the professor presents very well and easy to follow. I like the exercises and snap quiz within videos. One of my best course so far on Coursera.
Un acercamiento a modelos matemáticos para hacer estimaciones bastante interesantes, con un método de enseñanza agradable mostrando aplicaciones frecuentemente a cada tema enseñado
This course did a great job of covering many topics and explaining their applications so that you can use the tools in real world scenarios.
Great course, good topic material and examples and well taught. Overall it was useful and relevant.
Highly impressed with the methodology and concepts given by the focal person... Thanks and Love
Thank you De Liu, I thoroughly enjoyed this predictive modeling hands-on tech course !
A well planned course on predictive modelling with hands on practice on MS Excel.
Demasiado importante todo lo que enseñan.Muy practico para la vida profesional.
Informative. Really liked the spread sheet examples.
Great Thank for sharing precious Information.