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Вернуться к Applied Data Science Capstone

Отзывы учащихся о курсе Applied Data Science Capstone от партнера IBM Skills Network

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Оценки: 6,353

О курсе

This is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python Specialization. This capstone project course will give you the chance to practice the work that data scientists do in real life when working with datasets. In this course you will assume the role of a Data Scientist working for a startup intending to compete with SpaceX, and in the process follow the Data Science methodology involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting your results to stakeholders. You will be tasked with predicting if the first stage of the SpaceX Falcon 9 rocket will land successfully. With the help of your Data Science findings and models, the competing startup you have been hired by can make more informed bids against SpaceX for a rocket launch. In this course, there will not be much new learning, instead you’ll focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your data science and machine learning portfolio to showcase to employers....

Лучшие рецензии

LD

23 окт. 2019 г.

Its was great experience in completing the project using all skills that we learned in the course, thanks to coursera and IBM for giving me an opportunity to update my selft and also to test my skills

SG

3 мар. 2020 г.

Very good capstone project. Learnt lot of insights on how to represent data through out this course.

Very good starting point for ""Data Science" field. I would definitely recommend this course.

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76–100 из 858 отзывов о курсе Applied Data Science Capstone

автор: Yibing S

10 июля 2019 г.

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5 дек. 2021 г.

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26 апр. 2019 г.

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14 мая 2020 г.

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5 нояб. 2018 г.

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21 окт. 2021 г.

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18 апр. 2020 г.

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24 сент. 2019 г.

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7 февр. 2022 г.

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14 дек. 2020 г.

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21 янв. 2020 г.

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27 июля 2022 г.

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29 июля 2021 г.