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

3.6
stars
511 ratings
184 reviews

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

TM
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.

NC
Jun 4, 2020

Excelent! Even for someone that doesnt work usually with statistic models, this course give the fundamentals insights so that we can go deeper by ourself.

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101 - 125 of 182 Reviews for Predictive Modeling and Analytics

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 10, 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 Mohana P L

Apr 1, 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.

By Jaishish

Aug 15, 2020

Don't mind the negative reviews. Most issues are years old and have been fixed. Didn't face a single issue. The course Does require an additional tool to complete assignment which is only free for 15 days. Also the accent of the professor is hard to understand.

By Shafeeq S

Jan 11, 2019

Very good course for understanding Regression, classification. Other advance predictive models like trees, random forest, neural networks are covered fast. Could have been little more lengthy sessions.

instructor is very fast in explaining concepts.

By PRATIK J P

Sep 13, 2020

The instructor's tone was difficult to Interpret. It was not fluent and pronunciations were uneasy. Overall content was excellent, though there must have been examples after terms explanation rather than one complete video at end

By La V M

Oct 3, 2020

The course is a great course.

The only difficulity I had was in the last assessment where we had to use XLMiner. I was not able to use it properly as I had difficulity loading it on my computer because of the Windows version.

By Yashasvi

Jul 24, 2020

it is really a good course which helps me to understand the basic knowledge of data mining in which I learned about logistic and linear regression and also about boosting, bagging, and random forest.

By Rhonda M

Sep 10, 2019

Professor is a little tough to understand, so I had to read the transcript during some of the videos. However, once I got the XLMiner issues resolved, it continued to be a great class and experience.

By Cayla C

Sep 9, 2018

Really like the course and learned a lot. Wish that the quizzes didn't offer as much guidance on the steps to use XL Miner. Because this is given, it's not fully testing students on the material

By Miah M Z

May 30, 2020

A good introduction to various techniques of predictive modeling. To better understand, further study on the topics is necessary.

By Patrick C

Nov 10, 2020

some items were unclear, the definitions, the explanation, the examples were necessary. however, I could google to get those.

By Pelin T

Aug 10, 2020

Although the material presented in the course was very useful, it was hard to keep up with the instructer.

By Thejes S V

Nov 21, 2016

The Case Assignments are pretty useful

By SOUMYA B

Dec 9, 2017

very well explained

By Akintan O

Mar 13, 2017

Tricky to Pass

By Santiago F

May 12, 2020

The course although presents great topics, it needs improvement to support students with questions about exams and assignments. I'm not gonna sugar code this review, it took me hours and hours of dedication to pass the quizzes and assignments, and did not get much help from the professors, one of the instructors has poor English skills and is very hard to understand his lectures. However, this course presents you a challenge to better yourself, believe me, if you spend the time, read the questions that other students post in the discussion forum, and follow the guidelines from the videos, you'll pass. I struggled at the end but ended up getting 97% in my final grade. One advice, keep track of the correct and wrong answers you get from the quizzes, many questions repeat themselves, take notes from the videos or ppt, is not enough just watch, be an active learner and you'll be fine.

By Chris m

Sep 28, 2020

Instructor wants the students to learn but the method of presentation and practice doesn't align. The software required uses an outdated software that many users struggle to obtain and install. The lectures do provide some visuals but the amount of information flooded to the student is overwhelming. The quizzes need a improvement, almost all require the use of XLMiner which is complete rubbish. I suggest requiring the students to get familiar with the formulas rather than use a tool which results in a black box scenario for the learners. I do appreciate the time and effort put forth but providing the most current and up to date method of learning is the better option.

By Otto C

Aug 12, 2020

I think it would be more helpful to fully explain an example of how the techniques you learn help you to solve problems. I think that I learned the basics of the regressions and trees but I wouldn't know what to do after you get the results, maybe the example could include what you do next after you get the results from XL Miner. Professor Dan is a really smart person and you can definitely tell he know what he's teaching, however I think he could be more friendly to the camera and maybe smile more :)

By NAGABHAIRU V K

Jul 5, 2020

I really want to mention two thing about this course. The first thing is the content (Algorithms) which are talked in this course are Really usefull and important mostly used algorithms to learn clearly.and another thing is the instruction was so bad in explaining the subject .He is so fast in explaing concepts and math beahind it .Even not only he is fast his native english pronosation is so bad and its really tough to understand.

By Emiljo J

May 14, 2020

I found the course content to be good and explanations to be concise but sometimes rushed through. The choice of software to use, however well aimed as it did not require manual programming, it proved a more frustrating experience than actually writing it in Python. I also hardly believe that I would be using Analytic Solver in the future.

By Thu

Mar 24, 2020

A good course overall; however, I expected some further reading recommendations by the lecturer to help develop a deeper understanding of predictive models.

The last peer assignment was boring and too simple relative to the course knowledge level. Plus, one of the tasks was replicated from another one that I previously did.

By Matthew G

May 15, 2020

Covers a lot of essential topics around analytics and predictive modeling. However, the delivery in the lectures lacks enthusiasm and seems very scripted. Also, the final project, despite being primarily a predictive analytics courses is simple a re-hash of the Week 1 project, and is not cumulative of all topics covered.