Learner Reviews & Feedback for Predictive Modeling and Analytics by University of Colorado Boulder
About the Course
predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which
refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry
out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business. You’ll also
learn how to summarize and visualize datasets using plots so that you can present your results in a compelling and meaningf...
Top reviews
TN
Apr 15, 2020
Good course to give a basic understanding of predictive modelling and analytics. Good assignments and opportunity to review peer submissions help reinforce the learnings.
OD
May 30, 2019
Even though a basic math background is needed, this course is extremely simplified for understanding and being really useful introduction to Predictive modeling.
101 - 125 of 217 Reviews for Predictive Modeling and Analytics
By Rodolfo M C
•Jul 11, 2022
i like the course because it is practical
By Emmanuel C O
•Feb 18, 2020
Great Course... Very useful learnings...
By Adekunle I
•Jul 27, 2020
this is the best course anyone can take
By Ivan Z
•Jul 29, 2018
Dan Zhang is a very good teacher.
By Rashmi P
•Jan 6, 2022
Very informative course
By ANKIT S
•Jun 19, 2020
Detailed and usefull
By Murodkhuja M
•May 5, 2020
excellent course
By Avinash T
•Aug 28, 2017
Very nice course
By Tanay C
•Nov 27, 2017
its really good
By MOH M Y S
•Oct 5, 2020
Great Course !
By PRALAY P
•Apr 29, 2018
Great Course !
By Sandhya K
•Jan 3, 2017
Well explained
By Carlos A U M
•Jul 11, 2020
Great course!
By Sergio A M O
•Jun 5, 2020
Great course
By Jorge L P R
•Feb 25, 2021
Excelenete
By KM I P
•Sep 19, 2023
well Done
By Olanrewaju B
•Jul 16, 2020
its hard
By Ameerah
•Sep 9, 2017
awsome
By P. H
•Sep 3, 2024
Good.
By EMAD A A A
•Sep 21, 2021
good
By Germán A R R
•Aug 10, 2020
Overall is a practical and interesting course. Sometimes the quizes or assignments are not direct related to the lecture, however you can get to the point thinking a little. Will be important to update the XL Miner explanations because the software is currently more up to date than was shown. Additionally, even we get lot of practical exercises where you can identify robustness and types of models, for me is not still clear how to get a predictive model for my daily use. Expect to cover that on further lectures.
By Eric Z
•Apr 11, 2019
I really enjoyed this course, but I did struggle more than I should have with the software tools. In many cases, my version of the tool (the latest) did not match the instructor's version, and I worked to translate my version to his, and that's not a good use of my time. That said, the material was interesting, and the professor did a great job presenting it. I would recommend the course, but I would recommend that you learn to get the results not just in XL Miner, but in R or some other software, as well
By Butterfly g
•Apr 2, 2021
This course mainly aims at someone who knows about econometric regression and basics of ML algorithms. To me, I had little problem in understanding some concepts in ML as I didn't know all algorithms in detail. However, I put effort to read the basics of each algorithm and then watched the lectures. Thank you Professor Dan Zhang
By Colin P
•Oct 4, 2018
Very interesting course that covers a lot, which is good in that it gives exposure to different mining techniques, but bad in that I feel very far from mastering the techniques. Each mining technique could be its own course. Course could do a better job of explaining how to interpret the model outputs.
By Haiying Z
•Dec 28, 2020
The knowledge and information are very useful. However, the choice of software is poor. It took a few times (days) to install/uninstall to make it finally worked. Once it was running, it was unstable, malfunctioning unpredictably. A better software should be use for this class in future.