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Отзывы учащихся о курсе Predictive Modeling and Analytics от партнера Колорадский университет в Боулдере

3.7
звезд
Оценки: 450
Рецензии: 160

О курсе

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....

Лучшие рецензии

TM

Apr 15, 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.

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.

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26–50 из 158 отзывов о курсе Predictive Modeling and Analytics

автор: Mithun M

Jun 25, 2017

The instructor is really fast and he needs to slow down with better illustration.

автор: Wallace O

Jul 11, 2017

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

автор: Kevin S

May 24, 2018

Hard to follow seamlessly with poor pronunciation.

автор: Alan D P

Jul 17, 2020

This was quite a theoretical course to a certain extent - not as practical as the other courses in the Specialization. I don't think that this is material that I would envision me using normally in my work, but I can see where it might be useful.

The lecturer was hard to understand a lot of the time. He went past some important points at light speed and it was very hard to pick up certain concepts. Hard to take it in at times.

Repeating what others have said - I really didn't like having to use a specific software package rather than a generic package. XLminer can be obtained on a 14 day trial, however the course is intended to be 4 weeks long, so either do the course faster (like I did) or pay for a package that you will most likely never use again. The course is, to a large extent, a tutorial on XLminer and it's fair to say that most people that do this course will never use it again.

This course could do with a re-vamp.

автор: 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."

автор: Giuseppe B

Jul 07, 2020

I think this course has a very limited utility:

1) It's mainly referred to XLMiner, which is an excel add-on with a 15-days free trial. I think 99.999% of us will never use XLMiner again;

2) It's too much focused how to use the XLMiner tool, while the "content" part is rushed in some lessons

3) The framework is totaly absent: no business applications provided, no "why"/context but only tools

I found very tough to find useful takeaways, with a lot of untapped potential for this course.

автор: 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.

автор: 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

автор: 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.

автор: 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.

автор: 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.

автор: 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.

автор: Graham C

Mar 21, 2019

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

автор: Parv A

May 17, 2019

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

автор: Neeraj V

Nov 21, 2016

Cannot understand the diction..

автор: Lei Z

Dec 30, 2016

poor quiz design

автор: Graciano P

Sep 24, 2020

This class provides a solid foundation on predictive modeling and analytics. It goes from basic models like linear regression to more complex models including neural networks and ensemble models. The material is covered using a tool named Analytic Solver which provides a different approach to the subject by focusing on the high level aspects of the models as opposed to doing the models in Python which would require the ability of the user to code and knowing how to use the many libraries out there for data science and machine learning. This allows the learner to cover a lot of techniques in relatively short period of time while at the same time providing the learner with a broad vision and understanding of the field of study.

автор: Carolinne O R M

Sep 25, 2019

Very rich and concise content, instructor very intelligent and objective, short and digestible videos. My only suggestion is to improve the quality of the neural network content, in my opinion, the very one too shallow compared with the rest of the excellent content.

автор: Carlos J G A

Jul 17, 2020

Nice course, maybe you can update the instructions, the program has changed a little bit, is not difficult to change some parameters but it would be better with this video updates in XLminer activities. Thanks U Colorado Boulder and professor Dan Zhang

автор: Shalmali C

Sep 16, 2020

The course was really good and informative. A lot more ways to analysing data than one would normally come across and a good explanation of the various concept.

One suggestion would be sorting out the XLminer subscription of excel versions above 2016.

автор: Meenakshi J

Jun 20, 2020

Very challenging but very Informative course. I think this course is good stepping stone for anyone in interested in analytics career. Prof Dan Zhang also pointed to some books and websites which I found very helpful.

автор: Thahir N M

Apr 15, 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.

автор: Emma w

Jan 14, 2020

This course talk about basic concept about preditive modeling and idea which you need to concern on. And the quizes are so great that you could practice what you learn.

автор: Oleksandr D

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.

автор: Nuno C

Jun 05, 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.