Chevron Left
Back to Applied Data Science Capstone

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.

Filter by:

951 - 975 of 992 Reviews for Applied Data Science Capstone

By Jeff H

•

Mar 14, 2022

good course until the last week where there were too many competitive non-intellectual tasks

By Piotr M

•

Jun 11, 2020

I didn't like that we had to use Foursquare — I could not come up with anything interesting.

By Siddhant S

•

Apr 2, 2020

The difficulty could be increased and the scope of topics covered could be wider.

By Tarikul I

•

Aug 9, 2022

I do not find the certificate although I have completed this course.

By Mbongeni N M

•

Feb 13, 2019

The instructor of the capstone saved this specialization for me.

By Ozkan K

•

Sep 15, 2019

I did not find the project relevant to the rest of the course

By Ros R

•

Nov 11, 2020

It is difficult. I will like more support from the teachers.

By Tomasz F

•

Dec 29, 2021

Expectations of final presentation are not quite clear.

By Alberto I A

•

Dec 23, 2019

Broken links in samples and csv data files.

By Shawn H

•

Jun 30, 2023

Instruction is not clear here and there.

By Ramakrishnan S

•

Jan 23, 2021

Didnt complete the project, Un enrolling

By Rebecca L

•

Mar 29, 2022

Not really elaborate for a capstone.

By Artem R

•

Nov 5, 2021

Long time check of the submissions.

By Charles J

•

May 3, 2020

some lab codes cannot run smoothly

By Abdul M A

•

Sep 25, 2019

very vague with the information

By Amey S P

•

Feb 11, 2020

It is good for beginners.

By Akshay I

•

Jul 25, 2020

Hardness Level High

By 赵圆方

•

Mar 16, 2019

really difficult

By Scott W

•

Jun 16, 2021

This review was written after taking the other courses in the IBM Data Science certificate.

The certificate as a whole is well worth it, in my opinion, and I feel like I learned a lot about the different aspects and methods to data science, which makes the way this particular course is written all the more baffling.

I have no idea why, after weeks or even months of learning about all these different data science aspects including machine learning, SQL, and other topics, this finishing course is almost entirely centered around the FourSquare API and being forced to use location data specifically.

This course in particular needs a rethink, especially in the subject matter department. Instructions in the labs are vague, and in some cases, don't even work properly. Code is given without explanation of what it does. Only one person needs to grade your project for you to get the final grade.

By far the worst course of the entire certificate.

By Jacob W

•

Dec 19, 2022

Covered a wide range of topics across ML, statistics, data visualization, analytics, and more. However, there was not nearly enough application-oriented aspects of this certificate. There were frequent technological errors, as well as errors in the wording of problems and inconsistencies between the lessons and the labs. All in all, I feel like I was given a high-level hint at understanding a wide range of topics, but I don't feel confident in my ability to head into a new project without basically relearning most of it. I've done other more application-oriented projects before for free.

By Hailu K

•

Sep 10, 2021

It serves better as a review project than threading all previous courses than as a real project. Especially that the final report is just ridiculous... No one in real working situation would submit such a report: they'd upset their stakeholders.

By Seth C

•

Jun 16, 2024

As with every Joseph Santarcangelo course, there is good outline of what to learn, but the communication skills and expertise of the staff are highly questionable. I always end up doing more learning outside of the class than I do in.

By Pablo D B

•

Jul 30, 2019

It would have been better if the assignment were split on previous courses. IMHO, this course was way longer than the other courses of the specialization

By Diego A F P

•

Jun 16, 2020

Many errors in the lab and some code were not properly explained. The quality of this module was not as good as the others.

By Karol S

•

May 16, 2020

One of the worst mooc ever, content outdated, lessons not real life, and absolute lack of feedback on final assignment