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Learner Reviews & Feedback for Applied Data Science Capstone by IBM

4.7
stars
6,960 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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51 - 75 of 959 Reviews for Applied Data Science Capstone

By Naga M

•

Dec 16, 2018

This is a very useful capstone project in which you can apply all the learning you have done throughout the course, the more practice you do the more you learn. I like this course from coursera and recommend it for data science aspirants.

Thank You!

By David M

•

Jun 6, 2020

This Program was well structured, it was a great combination of learning and problem solving. You also got a great chance to see how useful data can be and how easy it is to make it work for you

By Jamiil T A

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Mar 30, 2019

A must take capstone project. Enroll for it and you will be moved by the project... Very interesting !

By Nam N

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Sep 16, 2021

Good, but the last peer assignment, the report slides, that's so weary to do. It took me a week to do that boring task, I think they could make it more interesting with another way.

By Daniel D

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Sep 22, 2021

A good level of challenge, didn't need the 50 slide PP.

By Song N W

•

Apr 3, 2022

My review after around 11 or 12 months of studying all ten courses is: the IBM Data Science Professional Certificate contains general information and process on data science, but does not go into great detail. After joining the course, I was able to further think and ask at work how data collection would affect our product and indicate how the envisioned data may provide misleading information. However, the courses' duration is much longer than indicated on Coursera and apart from the time spent on completing the course contents, I have spent a lot of time trying to get Watson Studio or the hands-on lab operational, and the hands-on lab could be down for a week or more. From my perspective, this is counterintuitive and inefficient, and I did not expect this from IBM's products. Looking at some of the reviews for this course, I think it is fair to warn others who are looking to join that the courses are generic and some - if not most of the - time requires the learner to Google answers for any confusion and code tutorial or read books; this does not bother me as it has been my approach for a long time. As I am writing this review I am awaiting my classmate to review my peer assignment for the second time because I got less than the required pass grade, which perhaps my classmates may have experienced once or twice throughout these ten courses due to incorrectly marked assignments. Although I admit I did not perfectly complete the capstone project's slides, based on the guide I would have received a higher score than what I had; for example, I got zero points instead of two points for having my GitHub link and PDF file attached. However, I understand the importance of reading your peer's assignments because some of the assignments I read inspired me, but the peer-review system is flawed because the course expects a constant number of students studying at the same period and the minimum number of assignments required the students to review would cover the whole cohort for that period; evidently, sometimes this system does not operate as expected because there are usually threads asking for help to review the assignment on the week's discussion forum. Consequently, from my perspective, this course would be more efficient if an automated correction system was also available, similar to "Machine Learning by Andrew Ng".

By Pradyumna V M

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Oct 30, 2021

The topic is so far away from what we normally face in the business world that I found it irrelevant. Also, the whole course material (entire Data Science Professional Cert program) needs to be ''audited" for correctness, for example some quiz answers are wrong (therefore when you click the right answer, you get marked wrong), then there are instances of lack of guidance or misguidance in certain lab assignments, leading to hours of wasted time until you figure it out. Anyway it facilitates learning, albeit in a time-intensive way. Lastly, in case you need to quickly contact some instructor to point out anything, it's totally hopeless. Just give up. They make sure you cannot get in touch with a human being live. On the other hand, the course is organized well in terms of topic by topic development; a lot of effort has gone into creating the videos etc. I learned a lot and am happy with what I learned.

By Sobhan A

•

May 6, 2020

I can say overall it's a good program. However by reviewing the first few courses, you will get a headache, but the rest courses are very useful. Some parts are really useless for a data scientist and are more useful for programmers, which I recommend you do not put a lot of time on them and skip them as much as you can.

Apart from the material, I think this certificate is really useful for you to get a job. But, if you just want to learn new concepts in data science and do not need a certificate, I recommend you to take other courses other than IBM. There are very good courses on @linkedin Learning.

In this program, IBM pushes you to work only on its platforms which is really annoying and I think this a considerable drawback of this program.

If you spend at least 4-5 hours a day, you'll be able to complete it in 2 months. The subscription is monthly and it's around $50 CAD and you can unsubscribe whenever you want.

By Zach S

•

May 15, 2021

This course appears to be all but abandoned by IBM. Many components of the Applied Data Science Capstone are outdated, Pythons scripts won't load, with errors plaguing almost every assignment. The only assistance you'll find is two to three year old forum posts, unanswered, from students who had to overcome the same errors with strange workarounds. Not to mention, the instructions are abysmal. It's almost as if the creators of this course have never actually had a homework assignment, and simply don't know how to compose a homework assignment, or they didn't take the time to actually do it themselves. Again, lackluster data science course from IBM, that they themselves don't care about.

By PRZEMYSLAW G

•

Dec 7, 2021

While I rate highly the first 4 classes of the course, the 5th which is the final project is a joke.

There, you have to gather the info and make the predicition. Yet, you have a sample of, warning, 90 records and using ML models for that is a WASTE!

Also, the 5th does not treat crucial parts of DS jobs like feature engineering, picking right models or smply fitting the data correctly. In some cases it is not even there.

I do am sorry to grade it as 1/5 but the gem course class should be done better, way better.

By Daniel B

•

Nov 4, 2021

Utterly frustrating. Materials / deliverables change regularly so you I've ended up needing to restart twice. Course is poorly curated, basically just leaving you to debug code rather than really teaching you about data science.

Moderators ignore you (or simply don't exist?)

I regret being on this course for such a long time and wasting so much money. There are much better courses out there. This doesn't deserve the IBM brand.

By Javier J

•

Aug 20, 2020

There are a lot of things wrong with this course: The labs need to be updated, we are asking to do something that didn't work in the labs. We are also ask to submit links, and the submission box does not allow clickable links. The Quizzes that doesn't show the question, the all or nothing peer reviewers, all of this is in the discussion forums, but there is not enough support staff.

By Varun C

•

Aug 6, 2020

One star for the fact that the Lab notebooks were flooded with errors, you would need more time fixing the errors rather than going through them,

Also, in peer graded assignments, some of the links submitted aren't processed as hyperlinks and cannot be copy pasted either, so there's no way to view them.

Very bad experience on this one.

By Dennis M K

•

Oct 11, 2020

This obscene deadlines are impossible to say the least. If you wanted us to pay you the two months immediately you could have just stated it on the terms... I would rather pay all the three months worth of tuition immediately than wait almost to months to finish this course.

By Kendall L

•

May 23, 2020

This was the most frustrating course I have taken on Coursera. The foursqure api is not up to date and I had to waste hours of my life fixing the bugs.

By sohini s

•

Dec 30, 2021

Unnecessairily complicated. Here to learn Python..not how to connect files from here and there

By Gurvinder S

•

May 4, 2021

peer reviewing is worst

By Muhammad F S

•

May 9, 2020

It has been a fantastic journey of completing the 9 course specialization over the past two months!

I practically started with no prior exposure to data science but learned a lot of useful Python skills, tips-and-tricks, and knowledge about data science. The course material and instructors were excellent, and the Jupyter Notebooks were very challenging at times - at least for someone who had left programming around 15-years ago.

The specialization, as it says, is of beginner level but would definitely equip the students to move forward on their own in their quest for data science.

I would suggest adding courses on probability and statistics, linear algebra, and calculus in the specialization.

By Olin H K

•

May 16, 2020

What a wild ride! The IBM Data Science Professional Certificate was my first exposure to coding and Data Science. The courses prior to the Capstone really do give you enough rope where you can do some cool stuff for the Capstone Project. Throughout the program, I learned where to go when I needed to teach myself something, while I was exposed to the basics.

I'm probably not normal, but I spent 40 or so hours on the capstone project itself. Lots of Frustration at times, but lots of fun as well and I was proud of what I was able to accomplish.

By Hayford T

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May 13, 2020

When I started this course I didn't know how fast I could grab these concepts in Data Science, it has been a challenging journey, especially learning a new programming language Python with all the libraries and packages, but Don't underestimate the little efforts, It leads to greatness. Now through Coursera and IBM I can boast courses that has prepared and given me head start into my new career. Coursera has made it possible for me to study at my own pace. This is amazing!, it worth recommending!.

By Dario N

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May 17, 2021

The whole certificate is fantastic. It teaches you a great overview in many data science skills.

However, if you live in Germany, it will not help you get a job in the field at all - I mean AT ALL. It's completely worthless. You either need work experience in the filed or a Bachelors or Masters degree in statistics or computer science, but then again, you wouldn't need this certificate. So it's a great course to learn things, but it's a poor course to enhance your job opportunities.

By Henry W

•

Jan 28, 2021

This capstone course is what you make of it. I reviewed several final submissions (we are required to review one and optionally can review several). Some people made the extra investment to do more than just apply the labs to other cities, they really learned by applying all the past learning and doing a project to apply and showcase their learning. There is lots to learn and apply here. My advice is for you to invest all you can so you can showcase your abilities!

By Atfy I Z

•

Apr 27, 2020

A great course that tests your skills to apply your cumulative knowledge on Data Science since you embarked on the Programme.

As for me, even though I don't intend to become a full-fledged Data Science, this course along with the Specialisation Programme provide sufficient understanding and practical hands-on learning to better appreciate benefits and constraints of Data Science, particularly on the importance of data and machine learning ability.

By Dayli S

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Apr 30, 2020

I really like using everything I learned into my own example built from the beginning to end. I felt a little bit unsecured with the assignment at the beginning, because I was really a beginner in Python before I started this course. But it encouraged me a lot to finish it and to learn more. Now I have a basis and a lot of information, that I need to sort out. I am planning to do more Python courses and continue practicing.

By Julien P

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Feb 23, 2020

Great to put into action the theoretical knowledge acquired in the previous 8 classes. What could be improved? The peer-rating system can be very slow. A common practice is to go on the forum to beg for a rating by another learner. This can be tiring.