Xlminer student how to#
Xlminer student full#

The quiz questions really make certain that you have listened to and absorbed the course material. If you want your certificate, come back after two months AND KEEP PAYING!! I canceled my subscription, I do not want the certificate, I want to cooperate with organization that respect my effort, my time, my money, to respect me.ДЄ challenging course, the most challenging I've had on Coursera to-date. This is not a policy of an educational institute, this is an attitude that wants to take only your money. I contacted the customer service, they told me that they are sorry and they cannot change it. That means that I had to wait more than one month, and pay 2 more subscriptions to Coursera!!! In the forum of the class there are more than 20 moderators, none of them has even one reply in anything. In the last course needed to take the Specialization Certificate, the Advanced Business Analytics Capstone, the assignments of the course during the 2nd-3rd-4rth week were locked until 20 December - 5 January. I finished the first four courses in more or less 3 weeks.

Xlminer student full#

I took the Advanced Business Analytics Specialization as a full time student.

You have always to reed the subtitles to understand the course. Perhaps the instructor's version had different default values than the version I was using. I hate not knowing what I was doing wrong though. 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. 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. 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. 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). 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. the instructor did a good job of getting through it. In my opinion UC-B needs to rethink if they should even offer this course. If this had been the first course in the specialization, I would not have continued. Overall I was extremely disappointed and would not recommend this course to anyone. The Analytic Solver (the Add-Inrepresentative said the problem was on their end, and had to fix the issue himself. 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 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. The course also requires paying $25 for an Excel Add-In, which was not mentioned before enrolling in the course. There were no slides, so note taking was difficult. Even the transcript had the words listed multiple times because he was so difficult to understand. The professor was knowledgeable, but was difficult to understand and spoke quickly. The expected prerequisites for this course include a prior working knowledge of Excel, introductory level algebra, and basic statistics. The techniques discussed are applied in all functional areas within business organizations including accounting, finance, human resource management, marketing, operations, and strategic planning. This course is designed for anyone who is interested in using data to gain insights and make better business decisions. We will use a practical predictive modeling software, XLMiner, which is a popular Excel plug-in.

Xlminer student how to#

YouвЂ™ll also learn how to summarize and visualize datasets using plots so that you can present your results in a compelling and meaningful way.

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.

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. This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. Welcome to the second course in the Data Analytics for Business specialization!