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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: 6,131

О курсе

This capstone project course will give you a taste of what data scientists go through in real life when working with real datasets. 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 are tasked with predicting if the first stage of the SpaceX Falcon 9 rocket will land successfully. SpaceX advertises Falcon 9 rocket launches on its website, with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage. Therefore if you can accurately predict the likelihood of the first stage rocket landing successfully, you can determine the cost of a launch. 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. This course is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python Specialization. It is expected that you have completed all of the prior courses in the specialization/certificate before starting this one, as it requires the application of the knowledge and skills taught in those courses. In this course, there will not be too much new learning, and instead, the focus will be on hands-on work to demonstrate what you have learned in the previous courses. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course....

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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251–275 из 829 отзывов о курсе Applied Data Science Capstone

автор: Kevin C

21 янв. 2020 г.

This was a great course. Being able to apply all of the knowledge gained from the rest of the specialisation was great!

автор: Amol P

16 июля 2020 г.

It is good training session and real time example for fresher. thanks a lot to coursera for such type of certificate.

автор: Vivek K

2 нояб. 2019 г.

I Appreciate IBM to Provide me such a Platform. Awesome experience and learnt a lot of things. Thank you once again!!

автор: Joseph M

25 февр. 2022 г.

C​hallenging course, that allowed me to explore a lot more opportunity expansions for my focus as a data scientitst.

автор: Phan Q

2 окт. 2019 г.

The process helps me a lot not only in writing python code, but also create stories through report and presentation.

автор: Nicklas N

13 февр. 2019 г.

Hands on, a stumping project at the end, as well as lots of new skills and ideas to take with you. A real challenge!

автор: Cristovam B P

1 июня 2020 г.

Excellent course. Enjoyed it from the beginning to the end. Fabulous content and communication with other students.

автор: Georgiy M

27 сент. 2018 г.

The most interesting course from IBM ML courses scope. Due to tons of practice and interesting labs. Thanks, Alex.

автор: Lukas M

12 сент. 2021 г.

Amazing journey! This project was aewsome! Glad a did it.

I recommend this course so much. Thanks IBM and Cousera.

автор: L. F

20 авг. 2020 г.

As a summary and overall assessment of the entire IBM data scientist course, Capstone's project is well designed.

автор: Goh S T

9 мая 2020 г.

Project helps to deepen your learnings. I would totally recommend doing the whole Applied Data Science Programme.

автор: Sajesh S K

22 нояб. 2018 г.

Enjoyed doing independent assignment. I had to hunt for data prepare the csv file to be used and lot of research.

автор: Ankit k

8 апр. 2020 г.

A very well structured and comprehensive course.Good for people like me to make them familiar with Data Science.

автор: Jorge B P

20 янв. 2021 г.

It was very informative and well structured. I recommended for people with interest in exploring Data Science.

автор: Jose L M

9 нояб. 2020 г.

Excellent course. I don't have any knowledge before. I feel that I adquire great skills to start in this career

автор: Rubenka B

31 мая 2020 г.

I have a brand new job as a Data Scientist after working as an analyst for 2 years. Thank you Coursera and IBM!

автор: Jason J D

27 сент. 2019 г.

Good course! The capstone project helped me strengthen the skills that I learnt throughout this specialization.

автор: Christopher A B

12 дек. 2020 г.

Thank you to the instructors and Coursera platform developers for creating an engaging and challenging course.

автор: Venkata R S

13 янв. 2019 г.

Great Course to implement your Data wrangling and all the learning that you got through out the specialization

автор: José M F M

7 мая 2022 г.

This course is very important to those intending to work as Data Scientist. I strongly recommend this course.

автор: Georgios L

5 июня 2020 г.

The capstone allows a deeper examination of a problem and contributes to readiness to tackle real problems.

автор: BETA R D

12 апр. 2020 г.

I have gained a very good hands-on experience with Git hub, Jupyter notebook, and many libraries of python .

автор: Mo R

3 дек. 2019 г.

This course is a great place to apply all the concepts about Data Science that we have learned in 8 courses!

автор: Arunjith M

28 июля 2019 г.

This is where you apply what you learned. I must say it is challenging, interesting and absolutely great. !!

автор: Diana

3 июля 2020 г.

Very interesting assignment. The attendees can practice the important skills according to their own wishes.