Chevron Left
Back to Predictive Modeling and Analytics

Learner Reviews & Feedback for Predictive Modeling and Analytics by University of Colorado Boulder

570 ratings

About the Course

Welcome to the second course in the Data Analytics for Business specialization! This course will introduce you to some of the most widely used 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 meaningful way. We will use a practical predictive modeling software, XLMiner, which is a popular Excel plug-in. This course is designed for anyone who is interested in using data to gain insights and make better business decisions. The techniques discussed are applied in all functional areas within business organizations including accounting, finance, human resource management, marketing, operations, and strategic planning. The expected prerequisites for this course include a prior working knowledge of Excel, introductory level algebra, and basic statistics....

Top reviews


Apr 14, 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.


Nov 19, 2017

this course teach you about the technical of using tools for predictive modeling. very useful for you who want to learn the fundamental of analytics.

Filter by:

176 - 200 of 208 Reviews for Predictive Modeling and Analytics

By Ruslan K

Aug 31, 2020

Interesting course however, it was very difficult to understand the instructor. I've had to use the lesson subtitles and slide pack to study the material; then just used to play video lesson to be able to open the next lesson.

By Lokesh T

Jul 17, 2020

Its really hard to understand the instructor even subtitles mentions inaudible on many places. There should either proper presentations available or Coursera can redraw this course with another instructor

By Rutvik P

Jan 24, 2022

Explanation across the specialization is extraordinary , however this course is core analytics and statistical. A nin-depth explanation of results of models and more engagement is required

By Markanday R

Aug 18, 2020

The instructor rushed through the videos, explanations were not very clear. The material was not very in depth and the coursework was not that helpful in understanding the concepts.

By Eduardo R O S

Apr 1, 2020

The instructor speak to fast and it's hard to understand what he said too many times. The material in the course in not well done. I believe that the course needs to be remake.

By Manas K

Apr 17, 2020

Much below my expectation or the level and quality the other courses bring. There are so many areas within this course that could be improved.

By tan l d

Jan 6, 2020

The accent of instructor is too strong to understand, it's an unpleasant experience to have listen through the class.

By Faizan R

Jun 15, 2020

its very difficult to understand the accent of the person otherwise content is very useful

By Svetoslava K

Feb 2, 2021

The instructor is certainly knowledgeable of the topic but has no idea how to teach

By Vedad K

May 20, 2020

Assignments are interesting but the explanations and presentations are awful.

By Connor C

Mar 26, 2020

Could not understand the instructor and the information was not useful

By Urmika K

Aug 12, 2020

Didn't really like the instructor for this course.

By Pranay B

Jun 2, 2021

The faculty was really bad

By Dham S

Apr 24, 2020

poor content structure

By Kevin J

Jun 3, 2020

I don't usually rate applications, let alone courses, but this is the one course I was extremely frustrated at, and I saw that I was not alone in this.

First, assignment 3 is buggy, very likely because the version of xlminer is different (I ended up downloading xlminer from other available sources because the version this course gave did not work!!). Different versions including the partition result presentation and logistic regression step 1 appearance.

Second, xlminer is COMPULSORY and NOT FREE (free trial does not count). You can not even use other tools such as Python or R because some of the values asked in questions specifically require excel to get. I still don't get why xlminer can not be a free open source add-ins. Python and R's basic machine libraries are free, why isn't xlminer?

Third, this course is the PREREQUISITE to Advance Business Analytics, which I am more interested in. Combine with my second point, it's like locking a character in a game behind a paywall as a DLC, of course people would not like it.

If you are aiming for a certificate for this course, just forget it, it's not worth it. If you are aiming for learning the subject, you can still take the course. Overall, absolutely not going to recommend it.

To developer of this course, please REVISE THE ASSIGNMENT ASAP.

By Aman G

May 11, 2020

This class doesn't even deserve that one star.It is easily the worst class I've ever taken on Coursera. The data in the final does not match the description. There are mistakes in the lessons and on the quiz. There is no feedback to forum.I was very disappointed by this course. The professor was knowledgeable, but was difficult to understand and spoke quickly. Even the transcript had the words [INAUDIBLE] listed multiple times because he was so difficult to understand. There were no slides, so note taking was difficult. The course also requires paying $25 for an Excel Add-In, which was not mentioned before enrolling in the course. The Excel Add-In is a different version from the version used in the video, so it was very difficult to follow along because the screens and outputs were different. I also had an issue with the Excel Add-In that made some of my work late because the issue could not be resolved quickly. The Analytic Solver (the Add-Inrepresentative said the problem was on their end, and had to fix the issue himself. Overall I was extremely disappointed and would not recommend this course to anyone. If this had been the first course in the specialization, I would not have continued. In my opinion UC-B needs to rethink if they should even offer this course.

By Udita T

Jun 14, 2022

I am sorry to say this is the worst course I have taken on Coursera:

1. The course was recorded in 2015/2016 and the XLMiner add-in for Excel has been updated, it is no longer called XLMiner.

2. The course content is superficial - there are just approximately 30 minutes of video for each module. No concepts are explained, instead just number crunching is taught.

3. No answers to quizzes are provided so one doesn't know what the correct answer should have been. This does not make for effective teaching and learning.

4. The instructor speaks too fast and reads from a script. Again a huge problem when trying to follow his videos.

If this wasn't a required course in the Advanced Business Analytics Specialization I would have dropped this course. As it is, this course took me forever to finish as it made for some extremely frustrating moments.

Please do something!!!

By Lauri S

Apr 27, 2020

I learned close to nothing (I want to say it was absolutely nothing because I think that's accurate), from this course. In my opinion, it was just a plug for the university's data miner plug-in. The instructor was so hard to understand and the videos didn't instruct on how to implement the practices they "taught". Finally, I don't know anyone in data analytics who uses these methods of predictive modeling. They're outdated and school-level insights used by professors. I do not recommend this course to anyone.

By Trevor B

Jun 22, 2020

As if the professor's lifeless eyes didn't make it tough to focus on the videos already, the professor was incredibly tough to understand to the point where even the person captioning the video had to add "(Inaudible)" at places. I also had to spend 2 days just trying to figure out XLMiner because I didn't have Excel and then later XLMiner wouldn't let me log in. This course was a nightmare

By Michael R

Aug 4, 2021

Solver gave me a temporary license which quickly expired before I finished all the classes. I have contacted them multiple times. This course is honestly not worth the hassle of trying to get access to their software. The desktop version doesn't work on my computer and the 365 temporary trial quickly expired. This was one of the worst experiences I've had on coursera.

By Alexander H

Feb 3, 2022

The lecturing definitely needs to be improved. It is really difficult to understand the instructor. Sometimes it is easier to read the transcript than watching the video! Additionally some slides / graphs in the video are not visible at all. Compared to the first course of this specialization this was a big disappointment!

By Rafael R

Jun 17, 2020

If you don´t have a US credit-card to purchase Solver you are not allowed to continue studying.

It´s just impossible to use a Credit-card from another country. It´s annoying and a waste of time.

coursera / Boulder Uni should elect only software companies or partners able to supply all students.

It´s a shame.

By Erwin T

Oct 9, 2020

Narrative in video's is way too fast and very mathematical oriented.

Documentation is weak.

High demanding on tests with quizzes on course info + each week extra quizzes with assignments

Not good to follow due to bad English in video's.

By Piero A T

May 10, 2020

I do not like this course. The lecturer's accent is really difficult to follow and there are no notes for this course. I do not understand why it keeps online. University should consider changing the lecturer.

By Robert J

Apr 26, 2022

You get stuck after week 2 in the assigment, because the software needed is not allowed in all coporate enviroments. Explanations are nt non-native english speaker friendly.