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Opiniones y comentarios de aprendices correspondientes a Data Science for Business Innovation por parte de EIT Digital

4.3
estrellas
231 calificaciones

Acerca del Curso

The Data Science for Business Innovation nano-course is a compendium of the must-have expertise in data science for executives and middle-management to foster data-driven innovation. The course explains what Data Science is and why it is so hyped. You will learn: * the value that Data Science can create * the main classes of problems that Data Science can solve * the difference is between descriptive, predictive, and prescriptive analytics * the roles of machine learning and artificial intelligence. From a more technical perspective, the course covers supervised, unsupervised and semi-supervised methods, and explains what can be obtained with classification, clustering, and regression techniques. It discusses the role of NoSQL data models and technologies, and the role and impact of scalable cloud-based computation platforms. All topics are covered with example-based lectures, discussing use cases, success stories, and realistic examples. Following this nano-course, if you wish to further deepen your data science knowledge, you can attend the Data Science for Business Innovation live course https://professionalschool.eitdigital.eu/data-science-for-business-innovation...

Principales reseñas

UN

18 de ene. de 2022

Data Science is the future and this course has given a fundamental principles of this technology.

CM

15 de may. de 2021

Great course, great content, the quiz questions are tricky which makes it really interesting

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51 - 65 de 65 revisiones para Data Science for Business Innovation

por Rizqi F

26 de nov. de 2020

The course is good, but sometimes the quizzes are confusing.

por Jalu A D

14 de abr. de 2021

this course is great for introduction for data science

por Budi C S P S

3 de jul. de 2021

hard to understand the reading

por Joss H

23 de abr. de 2021

Good Concept! Thanks!

por OGUNJIMI O

27 de abr. de 2020

great

por Talles D C

1 de abr. de 2020

Good course to guide you to the basics of data science, explaining quite well the background for the basics of algorithms, statistics and machine learning. The questionnaire sections could be a bit better prepared, though, as I have had a hard time trying to understand what was expected for a couple of questions, due to what I see as unclear statements and alternatives.

por jordi m p

28 de ene. de 2021

Al contenido del curso no le he encontrado un hilo conductor, y algunos de los temas carecen de una introducción para entender la relación de estos con el curso. El tema más incómodo, y más fácil de arreglar, es la gramática usada al realizar las preguntas pues es confusa y te lleva a tener que realizar los test más veces de las que desearías.

por Aliyeva A

2 de ago. de 2020

The course was good for an introduction to Data Science but I had to do a lot of additional research to completely understand all concepts mentioned in the videos because the explanations provided in the video were not clear enough.

por Claudio S

8 de dic. de 2019

It was ok, comprehensive but only at a very high level. Concepts presented by example rather than with concrete explanations. English language was nominal with quizzes not well formulated.

por Mehmood

7 de jul. de 2020

Good course for beginners. The only problem is with the quizzes. All the quiz questions are beyond the scope of this course.

por KITTIKARN L

20 de feb. de 2022

It is hard for beginner who learn in the polical science field

por Shane S

19 de sep. de 2020

Good course material, but trickily worded quizzes.

por Leah M

15 de feb. de 2022

poorly-worded quizzes, some quizzes don't even have right answers, some questions not very relevant to the topic

por yogesh m

11 de ago. de 2020

This is an introductory course to machine learning.

por Wafa' H

11 de feb. de 2022

It's not as what I expected to be, I enrolled it because I wanted to get to konw and work with tools in data science I don't want this kind of theoretical information which I can find in books and in alot of other university courses. what I want is working with real examples , analysing and manipulate data and getting deep to extract what we want ! so I didn't complete it.