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Отзывы учащихся о курсе Code Free Data Science от партнера Калифорнийский университет в Сан-Диего

Оценки: 168
Рецензии: 53

О курсе

The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data. Predicting future trends and behaviors allows for proactive, data-driven decisions. During the class learners will acquire new skills to apply predictive algorithms to real data, evaluate, validate and interpret the results without any pre requisites for any kind of programming. Participants will gain the essential skills to design, build, verify and test predictive models. You Will Learn • How to design Data Science workflows without any programming involved • Essential Data Science skills to design, build, test and evaluate predictive models • Data Manipulation, preparation and Classification and clustering methods • Ways to apply Data Science algorithms to real data and evaluate and interpret the results...

Лучшие рецензии


22 мар. 2022 г.



21 июля 2020 г.

this course is so helpful for me as I am on the entry-level of data science learning.\n\nhowever, 1 questions on the last quiz need to be reviewed,\n\nThank you, Coursera!

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1–25 из 54 отзывов о курсе Code Free Data Science

автор: Alladina H

22 июля 2020 г.

this course is so helpful for me as I am on the entry-level of data science learning.

however, 1 questions on the last quiz need to be reviewed,

Thank you, Coursera!

автор: Carolina C F

16 июня 2020 г.

Great course, especially for those who have never had contact with Knime or with Big Data concepts before. I believe it will be very useful in my day-to-day work.

автор: Surendra D

19 июля 2020 г.

It's a good course for absolute beginners who want to learn "KNIME".

The instructor did a good job to cover the DS topics as well, however looks that she does not have time to reply you in Discussion Forums.

Issues - (1) the downloaded files did not have the column headers, (2) wording/language of some questions was ambiguous at some level, (3) nobody replies to the Discussion Forums

автор: Jose E A E

24 июля 2021 г.

The first week of the course is mostly irrelevant, and I suspect it was took directly from the lectures of the teacher.

The're serious problems with the subtitles, probably because of the accent of the teacher. In special, Knime is translated as "nine" in english and "nueve" in spanish.

The fourth week has a lot of material, compared with the first three.

Some of the dataset used has different versions, with different data, into the repository. It causes confussion and therefore produces to wrongly answer some of the exams.

I think it was a good idea of the teacher to introduce the jokes (y)

автор: Andreas S W

10 июня 2020 г.

It was difficult in the beginning of the course, but I enjoy the videos. It helped us a lot to understand and get used to the Knime Itself. It’s worth to try. I have no background in coding, but I can complete this one.


31 июля 2020 г.

This course is very awesome. If you are really interested in Data science i will suggest you must go for it.

автор: Paulo O M d P e S

22 сент. 2019 г.

Alguns exercícios e testes não possuíam informações suficientes ou precisas sobre as configurações a serem utilizadas, o que dificultava que os valores esperados fossem encontrados de primeira.

автор: kalikinkar

19 мая 2019 г.

Good over all information provided on bigdara

автор: Blaine S

14 авг. 2020 г.

It was interesting to learn about Data science and the basics of how to organize and view it, but there wasn't much help from the forums. So whenever you get lost you have to review all the videos and chapters by yourself. I would recommend doing the version for the sake of learning it by itself!

автор: Patrick B

16 мар. 2021 г.

the course is interesting, but no clear explanation/guideline for the answers of the exercises

автор: Codrin K

4 дек. 2019 г.

Assignments need to be better described and settings details or results can vary.

автор: César O H C

8 апр. 2021 г.

Audio vquality is bad, resources are hard to find in week 4 and there is no interaction with instructors

автор: Jim E

21 июня 2020 г.

Amazing introduction to data science and KNIME. Education is best when you can apply what you are learning, removing the need to code allowed me to focus on using the skills to solve problems, and not spend time googling coding questions.

автор: Amish A S

29 мая 2020 г.

A very nice , clear and concise introduction to the basic concepts and the Knime Platform.

It would have been even more exciting if there were further more advanced courses after this.

Glad that I took this course.

автор: Jayfe A A

28 окт. 2020 г.

I like this course since it gives me an operational overview on what data science can do on a large data. How I wish there is an extension to this course. Thank you!

автор: Marcio B C J

1 февр. 2022 г.

T​he exercises help to fix the commands.

T​he PDF's are great. Some are complex to who is starting, but in general they are understandable and useful.

автор: Ruban

18 июля 2020 г.

Wonderful course to start learning Data science.

Superb lectures.

Knime - great platform to work with

автор: Elif C Y

29 янв. 2022 г.

This is an excellent course. I really enjoyed learning data science with KNIME.

автор: Punam P

6 июля 2020 г.

Very nice and interesting Course.. Thank you team & University..

автор: Christian F C

24 сент. 2020 г.

Muy buen curso introductorio, dan ganas de seguir aprendiendo.

автор: Bhagya I

25 дек. 2021 г.

The best way to learn KNIME basics. Thank You Coursera !

автор: ไตรภูมิ ส

24 янв. 2022 г.

Easily to Understand and very Practical.


26 дек. 2020 г.

Exceptional Delivery and Content

автор: JAMES S Q

25 сент. 2019 г.

Very relevant course.

автор: Ajay K S

21 авг. 2020 г.

Excellent Learning