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Learner Reviews & Feedback for Applied Data Science Capstone by IBM

4.7
stars
7,126 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

OM

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The IBM Data Science Professional Certificate is a very good course. lam glad to have covered the course with the help of Coursera. I will put to use all concepts learnt in this Data Science series.

CS

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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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901 - 925 of 983 Reviews for Applied Data Science Capstone

By adetunji p

Feb 23, 2022

it was awsomee

By Deepak N

Aug 12, 2019

Good exposure.

By YIFAN H

Nov 10, 2019

真的难,对我这个初学者来说

By Angam P

Sep 15, 2019

great course

By Ernesto C M P

Jan 16, 2022

good course

By zoubair a

Jun 2, 2020

good course

By Magnus B

Jun 10, 2019

Fun course!

By Mustafa M M E

May 28, 2023

very good

By Abdulla M

Nov 6, 2020

very good

By Amanullah K

Oct 31, 2020

Excellent

By Satishkumar M

Jan 9, 2020

Average

By Prayag P

Jul 30, 2020

Good !

By Romero R J Y

May 25, 2024

nice

By Narmeen i

Sep 10, 2021

good

By Andrian R N

Aug 15, 2021

Cool

By Ben G

Aug 6, 2024

Let's start with the good: The activities. These are great reviews of what we have learned in other IBM courses, with some new stuff thrown in. I learned a lot. So why only 3 stars? The course has several basic problems that caused me to waste a LOT of time. 1) Unintelligible instructions/materials. There are so many grammar spelling errors, things copy/pasted into the wrong place, etc that it can be quite hard to follow. This is common in IBM courses but in this one I really felt it. 2) Technical issues. Labs crashed several times for me. In the Dash lab, it was particularly annoying, as the work cannot be saved in the lab itself, and so I lost all progress every time there was a crash. To make things worse, the staff moved several of my labs to different locations, forcing me to redo several hours of work (hopefully this is just a once-off problem though). 3) Some strange activities. For example, how does finding everything that starts with 'CCA' help us to answer the research question? Yes, it might be good practice in it's own right, but why can't we get practice by working towards the stated goal instead of by doing random time-filler activities?

By Tania D

Aug 21, 2020

The assignments were interesting especially when we had to think of our own problems to solve. It would've been really helpful if the course was regularly updated, specifically when it comes to the first assignment where a lot of students experienced challenges with their machines and the course was designed with old operating machines in mind. the discussion forums would help a lot if instructors actually answered the questions and not directed students to links that were of no assistance at all. The course material could really do with an upgrade.

By Thøger E R

Sep 14, 2022

The curriculum and project work was fine. Notebooks to complete were OK, although not flawless. The final presentation format was... bad. A written report in the form of a 50 slide PowerPoint presentation is *not* a good habit to be teaching future data science professionals. Plus the instructions regarding what was expected were either ambiguous, confusing, or absent. The curriculum is great and I learned something. The testing procedure was extremely tedious and poorly thought out and in dire need of a major overhaul.

By John F

Sep 14, 2022

Very prescriptive and guided. Everything I have come to expect from Coursera. Little room for critical thought or original content. Designed for begineers. I am surprised this is an IBM course beyond building the user base for its tools. The marking Rubik's are too prescribed to provide accurate marks which matters little given the way in which they are applied. The final powerpoint assignment should be replaced with a report and a ten slide deck.

By Marius S

Oct 14, 2020

The github guide was very helpful and informative. I wished there would have been more explanations how to interprete the results of evaluated models and about machine models in general, when to use which model for example. Also some details were missing like how to balance imbalanced data, should the data be balanced and then visualized or vice versa? Fitting a model is easily done, but it's the details that make the difference.

By Paulo R M d C

Oct 17, 2022

I went through many problems to complete the Plotly Dash labs which puts up a small HTTP server on a non-standard PORT. I had to setup an entire environment in my personal computer to work around them. Also, due to the lengthy labs of this course, many of my colleagues reported problems running out of CUH in IBM Watson environemnt. I believe 50% more CUH would suffice for this course.

By Deleted A

Jul 31, 2020

The course gives the learners a perfect platform to practice the concepts learnt throughout the Data Science specialization. Final assignment is unique and interesting and the course makes sure you practice enough before taking it up. A good experience, but issues with Foursquare now and then makes it a little hectic to get done with the course.

A nice course though. Liked it!

By PRANJIT G

Jun 2, 2020

The journey was very informative but at the end of the course and submitting all of my assignments before the deadline , i got my course certificate with no instructor signature . A very disappointing fact as I worked very hard to complete the specialization within my 7 day free trial which is till 8 pm today I.S.T

Never expected such kind of irresponsibility

By Shane W

Nov 18, 2020

The capstone content needs to be thoroughly edited for clarity, especially in the instructions on what exactly the instructors are looking for in the final deliverables. Some of the peer-reviewers seem to be confused, and I'll admit I was a little confused myself reading through the instructions the first time.

By Bart F

Oct 9, 2020

The final capstone felt like a mis-match with the previous 3 courses of the specialization. The capstone was also the final project for other specialization which would explain the mis-match.

Even though I learned a lot, it wasn't entirely clear what was actually required from me.