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Applied Data Science Capstone(으)로 돌아가기

IBM의 Applied Data Science Capstone 학습자 리뷰 및 피드백

6,007개의 평가
808개의 리뷰

강좌 소개

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....

최상위 리뷰


2019년 10월 23일

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


2020년 3월 3일

Very good capstone project. Learnt lot of insights on how to represent data through out this course.\n\nVery good starting point for ""Data Science" field. I would definitely recommend this course.

필터링 기준:

Applied Data Science Capstone의 812개 리뷰 중 226~250

교육 기관: WingSingLeng

2022년 5월 7일

Thank you so much, it was an interesting and the only part has to review was that some instruction was not clear or precise.

교육 기관: Brent A

2022년 1월 31일

A thorough recap of all aspects of the Data Science course set material. Enjoyed it very much and received a lot of value.

교육 기관: Lee Y Y

2020년 2월 9일

A comprehensive content and project makes me understand a lot how a data scientist works and presents in a sophisticated way

교육 기관: Snehal G

2020년 7월 6일

I love this course. The well-organized content and quick Coursera team technical quick support. Thank you for your support.

교육 기관: Hadi S

2019년 6월 14일

This course gave me a great opportunity to work on a practical case study involving data wrangling and predictive modeling.

교육 기관: Muhammad H

2021년 2월 18일

learning curve is a little bit steep but it's amazing and encouraging you to learn more and push yourself beyond limits :D

교육 기관: Shreayan C

2019년 11월 29일

Really informative course, got to learn many practical applications of data science and made a really interesting project.

교육 기관: Manula V

2020년 5월 28일

It;s a very good assignment for us beginners to start with Machine Learning and get hands on experience with Data Science

교육 기관: Tanmaya C

2020년 4월 28일

I just say that it's awesome to learn these thing via building with my own. Thanks for the course instructors & coursera.

교육 기관: Rodney C B

2020년 4월 6일

Good course and practice scenario that make use of the skills, tools and methods learned during the entire certification.

교육 기관: Anuar M

2020년 3월 29일

Excellent capstone project, it provides me with ability to apply what I have learned throughout the data science courses.

교육 기관: Yu-Chi B

2019년 6월 21일

It's a really solid course. Take me lots of time but also let me learned a lot. It can improve your self-learning skills.

교육 기관: Sébastien W

2019년 12월 3일

I found the level of the exercises and projects appropriate, at least what an aspiring data scientist is supposed to get

교육 기관: Kevin C

2020년 1월 21일

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

교육 기관: Amol P

2020년 7월 16일

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

교육 기관: Vivek K

2019년 11월 2일

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

교육 기관: Joseph M

2022년 2월 25일

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

교육 기관: Phan Q

2019년 10월 2일

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

교육 기관: Nicklas N

2019년 2월 13일

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

교육 기관: Cristovam B P

2020년 6월 1일

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

교육 기관: Georgiy M

2018년 9월 27일

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

교육 기관: Lukas M

2021년 9월 12일

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

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

교육 기관: Lingyan F

2020년 8월 20일

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

교육 기관: Goh S T

2020년 5월 9일

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

교육 기관: Sajesh S K

2018년 11월 22일

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