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Quality Score

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Overall Score : 60 / 100

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Course Description

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.

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Instructor Details

Dan Zhang

Dan Zhang is Associate Professor of Operations Management at Leeds School of Business, University of Colorado Boulder. Dr. Zhang teaches in the area of operations management and data analytics in undergraduate, MBA, and PhD programs. Courses he taught include Business Statistics, Operations Management, Advanced Data Analytics, Spreadsheet Modeling, Stochastic Dynamic Programming, and Pricing and Revenue Management. Dr. Zhang's primary research interest is data-driven decision making with applications to pricing and revenue management, supply chain management, and healthcare operations. He published 20 research articles on these topics and frequently speak at conferences, companies, and academic institutions. He consulted in his area of expertise for companies in Canada, China, Europe, and United States. He is the current president of the INFORMS Rocky Mountain Chapter, a society of analytics professionals in the rocky mountain region, and serves on the advisor board of Tech Valley Inc., a big data startup supported by Microsoft Accelerator. More recently, he was elected chair of INFORMS Pricing and Revenue Management Section, an international society of pricing and revenue management researchers and professionals.

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Reviews

3.0

65 total reviews

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By William C on 3-Jul-18

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 Rohan G L on 29-Jan-18

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. The instructor's English is of a very low level and he speaks entirely too quickly.Coursera, please delete this class. Look at the comments below.

By Yvonne G Q T on 16-Sep-18

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 Jennifer Z on 5-Jun-18

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 :)

By Pooja on 2-Jan-18

The instructor's accent is difficultto understand. The subtitles are also not helpful as sometimes it also misintreprets what the instructor is saying or writes(incoherent). The instructor is too fast and has explained concept too briefly. Many times I had to google to understand the concept and pass the quiz.Being a part of the specialisation, it is necessary to pass this course. However, the answers of the quiz are also sometimes not correct.I wish this course is thoroughly revised with some other instructor as it is very hard to understand with the present Instructor.The forum is also completely unresponsive.Please update this course.

By Abhishek U on 3-Aug-17

I liked the course information but it moves too fast. Week 4 module is too complicated to be covered in a 5 minute video. Many concepts should be explained in detail with examples. The teacher doesn't have a very easy accent to understand and there are many occasions when some really difficult concepts are covered in less than a minute. This course is fine to get basic understanding of predictive modelling but you need to study a lot on your own to truly understand the statistics behind them and concepts described in this course.

By Chinmaya M on 20-Nov-17

Its my individual perception about this course, reason of poor review1) The instructor is very quick, not sure what is intended to present2) The whole concept is based on XLMINER tool, which is free for 2 weeks. The tool is upgraded but the course material didn't.3) Quiz questions and answers, not sure if those are ever verified. Its very specific to older version of XLMiner tool.4) Not much support from moderator.

By Yihan W on 10-Mar-17

Week 3 application assignment is buggy. If you input correct answers they will be marked as incorrect. You must use trial and error to find the wrong answers the quiz is looking for. It's a badly designed assignment that wastes students' time and creates a lot of frustration. Would not recommend the course because of it.

By Lance R on 2-Jan-18

This course gave me a good understanding of the typical analytic tools used when doing predictive study. It has helped set the direction for my future business analytics study (don't expect to master all the topics in one short course!). If you don't already have a background in basic statistics you will probably struggle to understand much of the material. By basic I'm speaking of things such as basic hypothesis testing, error types, z scores, measures of variation and central tendency, confidence intervals, basic probability, basic understanding of logarithms and exponents.

By Arushi on 12-Aug-19

Got to many techniques like boosting, bagging, Neural networks, regression tress etc.. Useful and informative course

By Shivam S on 16-May-19

Really good course, The videos are very precise and short, lot of learning, Loved this course

By Mark S on 2-Jan-17

The instructor speaks too quickly and I think this will make it difficult for non-native English speakers to understand the material. This material will also be more understandable to individuals with a statistical analysis background, not enough time is spent on explanation and it will be necessary to supplement the class if you don't have the proper background. Passing the class by rote following of the examples will not give you the proper proficiency.