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Learner Reviews & Feedback for Applied Data Science Capstone by IBM

4.7
stars
7,165 ratings

About the Course

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....

Top reviews

LD

Oct 23, 2019

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

CS

Jun 15, 2023

It's a great course to get a comprehensive background on Data Science (including ML) and lays the foundation for more advanced courses. It touches on all the areas that are required for data science.

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776 - 800 of 992 Reviews for Applied Data Science Capstone

By silvio a

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Jan 18, 2022

nice

By dumebi j

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Oct 5, 2021

good

By Arpan C

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Apr 26, 2021

GOod

By Kasi V

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Nov 6, 2020

good

By Mohammed A W

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Oct 2, 2020

Good

By SHALINI S

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Sep 13, 2020

Good

By VISHNU T B

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Jun 28, 2020

Good

By Soumyajit D

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Jun 7, 2020

good

By A S R

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May 20, 2020

good

By Naveen S P

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May 10, 2020

BEST

By ARIJIT K

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Apr 28, 2020

good

By Ashneel k

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Mar 9, 2020

good

By iyyanar

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Jan 3, 2020

Good

By Manea S I

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Sep 25, 2019

nice

By Prabhu M

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Sep 17, 2019

good

By Gurnam S

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Mar 4, 2019

Good

By Mohammad I

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Mar 4, 2023

op

By Ikenna M

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Sep 8, 2022

ok

By Josh H

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Jan 12, 2020

AAA

By Talha A

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Sep 30, 2019

<3

By Koushika

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Aug 16, 2022

R

By Luis a l a

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Jul 31, 2021

f

By 林昀

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Apr 3, 2020

9

By Amy P

•

Jul 25, 2019

This is the final course in the IBM Data Science Certificate and it is primarily focused around a project of your choosing. First, you learn how to scrape data and use the Foursquare API, which is quite helpful as these skills are generally transferrable. Then you'll need to come up with an idea that is loosely related to location data in some way. You'll have several weeks to implement your idea and write a report and a blog post/presentation. The final project is a lot of work.

In my opinion, the grading system could be better. You rely on peer reviews to pass the course, but only one peer looks at your work. Multiple sets of eyes would be fairer and hopefully generate more feedback. The discussion forum aspect could also be improved to promote collaboration and not simply requests to "please review my submission".

All in all, a decent guided Capstone course. Be prepared to do a lot of work on your own as there is not a lot of structure or hand-holding. I am very proud to have completed a formal project/report that demonstrates how much I learned over the course of the IBM Data Science Certificate.

By surya m p

•

Apr 10, 2020

This course is excellent at teaching all the data science and machine learning skills from a practitioner's perspective. I would strongly recommend it to aspiring data science professionals. Other positives include free introduction to the IBM cloud platform.

Room for improvement include:

1. Improvement to reliability/availability of IBM Developer Skills Network (which was done towards the end of my course) or give it a miss (using IBM cloud platform instead) completely.

2. Assignments should be graded by instructors or through standardised testing. The current peer-graded system seems to be hit and miss. It is not ideal especially for such a long course.