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Opiniones y comentarios de aprendices correspondientes a Predictive Modeling and Analytics por parte de Universidad de Colorado en Boulder

3.6
estrellas
554 calificaciones
202 reseña

Acerca del 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....

Principales reseñas

TM

14 de abr. de 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

19 de nov. de 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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51 - 75 de 201 revisiones para Predictive Modeling and Analytics

por Akshat J

1 de ago. de 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 Karan G

20 de ago. de 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.

por Jon P

5 de ago. de 2020

Course quizzes and assignments are based around an outdated Excel extension that does not work anymore.

Week 3 quizzes have wrong answers.

por Ana H

8 de abr. de 2021

I would rate negative if I could.

HORRIBLE HORRIBLE QUALITY...Terrible really....... never would recommend it and just a mediocre class

por James M

22 de dic. de 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 Lam C V D

28 de ago. de 2020

Course using XLMiner, not Python. Poor choice. I used Python to get the results, all marked wrong!

por Graham C

21 de mar. de 2019

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

por Parv A

17 de may. de 2019

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

por Heino K

6 de sep. de 2021

This course is hard to follow for a non-naive English speaker.

por Neeraj V

21 de nov. de 2016

Cannot understand the diction..

por Lei Z

30 de dic. de 2016

poor quiz design

por Graciano P

24 de sep. de 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.

por Minh T N

1 de mar. de 2021

Good course for introductory knowledge about predictive modeling (linear regression, classification, trees, neural network, etc). The accent of the professor makes it a bit hard to follow, nevertheless the content and follow-up exercises as well as quiz assignments and case studies are of superb quality. Highly recommend for those interested in business predictive methods.

por Mauricio R s

15 de jun. de 2021

Me gustaria que algunos videos (los mas importantes) se explayen mas en la explicacion de los resultados para poder conocer en profundidad que significan cada uno de ellos y así poder interpretarlos. Por ej. que significa un r2 de 0,54 o que significa un RMSE de cierto nivel.

por carolinne r

24 de sep. de 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.

por Carlos J G A

16 de jul. de 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

por Shalmali C

16 de sep. de 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.

por Meenakshi J

20 de jun. de 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.

por thahir n

15 de abr. de 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.

por Emma w

14 de ene. de 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.

por Oleksandr D

30 de may. de 2019

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

por Nuno C

5 de jun. de 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.

por Harliano A

20 de nov. de 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.

por ADELEKE A A

7 de jul. de 2020

It has been very exciting and an eye-opening for me. I am getting into the world of data analytics gradually. Thanks for this great opportunity.

por sagar g

15 de may. de 2020

Very nice course, everything is up to the point very clean and clear explanation of concepts with examples and practical illustrations.