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Отзывы учащихся о курсе Python Project for Data Engineering от партнера IBM

Оценки: 221
Рецензии: 39

О курсе

This mini-course is intended to apply foundational Python skills by implementing different techniques to collect and work with data. Assume the role of a Data Engineer and extract data from multiple file formats, transform it into specific datatypes, and then load it into a single source for analysis. Continue with the course and test your knowledge by implementing webscraping and extracting data with APIs all with the help of multiple hands-on labs. After completing this course you will have acquired the confidence to begin collecting large datasets from multiple sources and transform them into one primary source, or begin web scraping to gain valuable business insights all with the use of Python. PRE-REQUISITE: **Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much instructional content. It is intended for you to apply prior Python knowledge....

Лучшие рецензии


1 авг. 2021 г.

This course is very challenged both Python skills for Extract Transform and Load assignment.\n\nI really enjoyed it.


21 сент. 2021 г.

Very informative, interactive and force us to learn and do the things on our own.

Фильтр по:

26–43 из 43 отзывов о курсе Python Project for Data Engineering

автор: Sharif

22 окт. 2021 г.

This may be irrelevant to this course but I need more exercises, to let me sharpen their new skill.

автор: Panagiotis B

12 июля 2021 г.

A well-structured course, but there were some misleading info in the labs.

автор: Siwei Z

23 июня 2022 г.

Good lessons, but I want more excercises, thanks.

автор: Smriti R

25 февр. 2021 г.

The couse is good for beginners

автор: Desmond C C H

11 мар. 2022 г.

The video lecture is insufficient to prepare for final assignments. The lab exercise scattered here and there. API, web scrapping, ETL lab and then final assignment. I felt if the video lecture could elaborate more on the terms like variable, built in Panda dataframe, how to pass into a function (recap on what we learn earlier previous module) using ETL example. This would help us prepare better.

Nonetheless, the discussion forum was useful. I am glad the search box is there allow me to input the search on topic I needed most. There were some logistics issue like jupyter notebook wget unable to work. If should have corner for new comer to go for, prerequisites. Let them know if they use anaconda jupyter notebook this is what they need. If they use win/mac then another approach. I spend some time figuring that out.

I have some assignment was thank to help from fellow peers. I wish the lecturer could more active share more hints on final assignments or others. Not many of us are good in programming.

автор: David M

5 мая 2022 г.

This is a good hands-on learning course. However, a certain portion of the existing instructions/design in the final peer-reviewed assignment causes an output that, if the student is not paying attention, will lead them to submitting incorrect results during the grading process. This really needs to be remedied, though it has been addressed in the forum. Make sure to reference the thread on the Extract step to avoid this pitfall! Also, make sure to import the notebook into the lab environment if you need extra time to work through any errors/difficulties/unexpected results because you could possibly max out your monthly Watson Studio Lite usage time in one afternoon.

автор: RY

17 янв. 2022 г.

The course content is good, but peer review is a bad choice. Peer review depends on everyone knowing what they are doing, but this is not always the case. It is time wasting to resubmit and wait to be graded again because of other people's fault. At least there should be a mentor who can help with the appealing process, provide feedback, or grade people who have to resubmit.

автор: Steven F O

19 июля 2021 г.

There were points of confusion in the hands-on exercises. A week of Panadas and perhaps a little deeper dive into Beautiful Soup would go a long way to make this a stellar course.

автор: Ariane D

9 сент. 2021 г.

Frustrating bugs when using the IBM Cloud. Unfair grading by peers. They do not provide an explanation of why they are grading bad when all exercises were completed as expected.

автор: Won D

12 мая 2022 г.

Instructions lack a bit of clearance. The videos are informative and done well. The overall concept is good and I recommend taking this course.

автор: Ilya P

25 сент. 2021 г.

too basic. Good for beginners

автор: Matt N

3 дек. 2021 г.

Not everything explained in as much detail as it could be. Some instructions out of date and some issues with IBM cloud error messages.

автор: Kyle S (

26 мая 2022 г.

This is the worst course on Coursera. It is a complete waste of time. If you wanted to learn how to read a file and slice a dataframe in pandas, I can teach you in about 10 minutes. If you wanted to sit through an interactive advertisement for IBM Watson, then I suppose this would be a good course for you.

автор: Alejandro L

26 авг. 2021 г.

Al parecer no hay ninguna explicación para realizar los cursos de webescraping. Me parece muy mala estructura del curso.

Apparently there is no explanation for taking the webscraping courses. I think the structure of the course is very bad.

автор: Lucy M

11 мар. 2022 г.

issues on the module

Peer Review Assignment - Data Engineer - Webscraping

and there is not key or cheat sheet. big problems with this one. please help.

автор: Sadique M

4 июля 2022 г.

Complete waste of time, got stuck with running codes as I am unable to use watson studio.

автор: Alejandra B V L

13 окт. 2021 г.

Need to explain more, it literally has no explanation at all

автор: Rets R

10 апр. 2022 г.

Error 400.

Many courses don't work :(