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Back to Predictive Modeling and Analytics

Predictive Modeling and Analytics , University of Colorado Boulder

3.8
157 ratings
49 reviews

About this 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

By HA

Nov 20, 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.

By SK

Feb 16, 2017

Its an excellent course and thanks to Professor for making this course so practice oriented.

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47 Reviews

By Isaura Duby Valdez

Oct 06, 2018

I only wished that the teacher would speak slower.

By Colin Paterson

Oct 04, 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 Yvonne Goh Qiu Ting

Sep 16, 2018

This module is badly organised and taught. The lecturer goes through the concepts with no explanation or illustration. As a result, it was hard to understand the significance and applicability of the concepts taught. It was also very hard to catch what he was saying as his voice was not clear and no slides were provided. Further, no answer key was provided for the assignments and quizzes - we wont even know why we got the question(s) wrong and what should be the correct step(s). The final assignment/quiz was kind of a repeat of the first four quizzes/assignments using a different set of data. While I appreciate that this is to give us more practice, it wasn't very useful as the lack of answer key for the first four assignments/quizzes meant that we couldn't quite know the reason for getting certain question(s) wrong earlier on.

By Cayla Cason

Sep 09, 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 Jordan Haas

Aug 31, 2018

The professor does not explain the concepts well enough, to be quite honest. I have simply used his videos as a way to Wikipedia the concepts to actually understand what he is trying to explain. Also, I think it would be beneficial to provide information prior to signing up for the course (or Advanced BA path) stating that there is additional content to purchase.

By Ivan Zaluzhnyy

Jul 29, 2018

Dan Zhang is a very good teacher.

By roshni rajput

Jul 09, 2018

I don't mean to criticize and I believe the content your courses offer is always great but I had difficulty with the instructor's speech delivery and his accent.

By William Carnes

Jul 03, 2018

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 Tracy Cacho

Jun 20, 2018

The material is fine, a bit rushed at the end. My biggest issue with this course is the lack of support when it comes to addressing system-related issues. I've had to resolve these on my own, because neither forums, Coursera, or Frontline Solvers customer care could help.

By Jennifer Zelmanski

Jun 05, 2018

Lots of info in 4 short weeks... the instructor did a good job of getting through it. I had issues with neural networks in XLMiner -- particularly, boosting and bagging; my in-Excel XLMiner wouldn't run models without terminating with an error. Using the in-the-cloud version of XLMiner was better because the menus matched what the instructor was showing in the videos (my desktop version did not). However, I never was able to get the right answer on any neural network boosting or bagging questions on any quiz, though I got all the other questions right - creating decision trees or logistic regression models through XLMiner, even boosting/bagging decision tree models, both Classify and Predict. There was zero traffic in the discussion forums (people were begging people to grade their peer assignments so they could get a grade) so there was zero response to my pleas for assistance. It was pretty frustrating. I finally got through the class because getting everything right except neural network boosting/bagging questions enabled me to squeak through with a passing score. I hate not knowing what I was doing wrong though. Perhaps the instructor's version had different default values than the version I was using. Oh well. It's in the past :)