Chevron Left
Voltar para Predictive Modeling and Analytics

Comentários e feedback de alunos de Predictive Modeling and Analytics da instituição Universidade do Colorado em Boulder

3.9
234 classificações
68 avaliações

Sobre o curso

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....

Melhores avaliações

AD

May 30, 2019

Even though a basic math background is needed, this course is extremely simplified for understanding and being really useful introduction to Predictive modeling.

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.

Filtrar por:

51 — 66 de {totalReviews} Avaliações para o Predictive Modeling and Analytics

por Kevin S

May 24, 2018

Hard to follow seamlessly with poor pronunciation.

por Naveed T

Nov 11, 2016

While the content (common predictive regression and classification algorithms and tools like XLMiner) was useful, little to no support was provided in the forums. The assignments in Week 3 and Week 4 in particular were either vague or had errors that nobody double checked and course-takers had to use trial and error approach to get answers right.

por Wallace O

Jul 11, 2017

Terms weren't very clear, and many videos had not txt file.

por Tony H

Feb 28, 2018

This course doesn't do a good job of helping you learn the "why" behind the concepts. I felt like a lot of difficult concepts were thrown at me with insufficient context. It's been tough trying to internalize meaningful mental models through the course content.

por teresa z

Jun 03, 2019

The content is useful. The lecturer is very good at organizing the course structure. However, he is a bad teacher. He reads subtitles instead of "talking". I hope he could elaborate key points and relate concepts to real life examples.

por Graham C

Mar 21, 2019

Very poor course and delivery of subject matter was terrible - Do Not Take This Course!

por MK B

Feb 27, 2017

This course is not well moderated, the material is confusing, and the quizzes were not tested before uploading them onto Coursera. This specialization is definitely not on par with other specializations I have done.

BLUF: There are better uses for your money and time.

por Jessica B

Nov 02, 2016

This course starts very simply with data clean up (almost too simply!), but then goes DEEP into the weeds of regression and fails to explain how to apply these complex concepts to any real world application. For example, if I build a regression model, how might I use it in my analytics role at work and explain the results to my stakeholders? How do i interpret the results of the regression for making informed business decisions? How do I predict an outcome with a Tree or Neural Network? I found the instructor very hard to follow/understand (thank goodness for the written transcripts). He's clearly extremely intelligent, but fails to relate these concepts to the student in order for the student to take away anything more than "These complex concepts and tools exist."

por Deleted A

Sep 29, 2017

poor instructor (too strong of an accent, no skills in talking with a teleprompter or generally putting life into what he says), material could be strongly improved, problems with assignments but no help in the forums

por Gökhan K

Apr 02, 2017

With all due respect to the lecturer (its obvious that he is intelligent and an expert on the subject), I found this lesson not easy to participate because of inordinate learning curve and fast accent.

por James M

Dec 22, 2016

Test questions for week 3 are incorrect and do not match video / reading. Had to go to YouTube to figure out most of it.

por Lei Z

Dec 30, 2016

poor quiz design

por Neeraj V

Nov 21, 2016

Cannot understand the diction..

por Akshat J

Aug 01, 2019

It's a terrible course. honestly. The Professor's English is very often undecipherable, assignments have incorrect options, and there's no help from anybody in charge. Would give 0 stars if possible.

por Parv A

May 17, 2019

Use of some other software can make this course better. xlminer has got a lot of bugs

por Karan G

Aug 20, 2019

Poor communication and engagement skills. The syllabus has so much potential to be interesting but the teacher wasn't engaging and left most of the important details unexplained.