Bewertung und Feedback des Lernenden für Applied Data Science Capstone von IBM

I hoped this course would be more complex but it mostly consist of Foursquare API requests. I had to focus how to fit other datasets in addition to Foursquare data to find something interesting but instead of using fancy algorithms and testing them I had to focus on data and it was really time consuming, I spent 2x more time on each assignment. Whole IBM DS path was great but final course was a big disappointment.

it was the worst Coursera course I've ever took. Course capstones pages are buggy, there are not adequate explanations at videos. The final project is very painful because there are not enough resources and you are forced to prepare "notebook", "report" and "presentation/blog post" can't we just prepare two of these items?

Issues with the lab sessions and untimely responses from the staff hindered my learning. Also, the students did not respond to my questions in the discussion forums, they seem to only be about themselves and having people grade their assignments.

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 Many components of the Applied Data Science Capstone are outdated, Pythons scripts won't load, with errors plaguing almost every assignment.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.

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.

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.

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.

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.

cannot unlock and continue studying after resting the deadline.

When I first started this capstone, it felt a bit disjointed compared with the rest of the courses. But after really biting into it, I realized the content makes sense: it allowed me to put to the test what I learned on the course. Being constrained to use the Foursquare API on the capstone feels a bit odd, but at the end using an API to get information works really well. I tried scrapping the information my self and the workload I put on my self became significant.

The only new machine learning tool introduced for this final part is K-means clustering, it's the most abstract concept on the entire specialization and I think it's the only one that could have been presented somewhat better. What I noticed while reviewing my peers is that for the assignments everyone (me included) would just copy the k-means clustering algorithm and repeat the same analysis used on the labs. Which is kind of a shame, I just wish K-means clustering could have been developed better, beyond copy-paste.

At then end it's you; the person taking this specialization, the one who decides how much work you're going to put into this.

Tough but ultimately very rewarding as you see your own data science project through from inception, to data pre-preprocessing, modelling and finally presenting. All in all, great course and a perfect way to round out an amazing specialization! Thank you IBM and thank you to all the course lecturers who contributed to make this high calibre program. This has given me the grounding and the confidence needed on my path towards being a data scientist.

Interesting project using Folium and Foursquare API. I learned a lot about geolocalization, and also pandas tricks, as i if you choose a subject on your own, usually your data sources are not cleaned (most of the time you got it by scrapping). Plan to work more than 20hrs (rather 30 - 40h) in order to complete the programming part (notebook and data analysis), the report (15 - 20 pages) and finally the blog article.

Enjoy it all !

Many thanks to all the teaching staffs for such interesting courses and diversified subjects. It was fascinating to learn something new each time. Sometimes there were technical issues with Watson Studio and code running mostly because of our lack of knowledge but sometimes real technical issues not depending on us. Thanks for teacher's help and peers' care to assist. I am satisfied with this 10 Module course.

O curso em si é bom, porém pede conhecimentos que não são passados durante o programa, e isso é algo inesperado, porém todos que querem trabalhar como cientista de dados devem estar preparados para contornar e vencer desafios diariamente. Então vejo como positivo essa estratégia de solicitar algo fora do escopo do treinamento. Pra mim foi muito bom, tive oportunidade de aprender coisas novas o tempo todo.

This course was challenging but rewarding. The setting up of the course was really quite frustrating but as everything continued I found myself incredibly engaged with what is going on. This course specialization was my first exposure to what are essentially programming skills and use of the Python language so it was really valuable to be able to produce a piece of work to demonstrate what I learned.

Thank you Coursera and IBM. I can now do statistical programming using different Python libraries, geospatial analysis using folium, notebook sharing via Github or IBM Cloud. Thank you for empowering me through sharpening my data management,manipulation,analysis and presentation skills. Certainly, the IBM Data Science Capstone has been one of the most worthwhile things I've done in 2020.

This Course is excellent and it gives Data Science,Methodology,python programming,Machine learning algorithims,Labs Excercises,Assignments and finally Capstone Project is worth to gain very good skills and knowledge.With this course I gained very strong skills and am now very confident in this Data Scientist field. Thank You Coursera and IBM for this course.

This is wonderful platform for enthusiastic Data Scientists aspirants to learn sophisticated empirical analysis to understand and make predictions about complex systems. Demonstrated methods and tooling from probability and statistics, mathematics, and computer science and primarily focus on extracting insights from data.

ThankYou

Hari Kumar G

Fantastic culmination of the Data Science Professional Certificate! This course provided excellent review in creating maps and using machine learning tools, and the final project is a great opportunity to practice many of the skills learned in previous courses as you analyze a real world data set of your choosing. Challenging and rewarding.

This is an excellent course. I had learnt the real-world applications of foursquare API and how we can find out the restaurants, coffee shops, shopping malls etc. within a particular neighbourhood and how to cluster them. I am completely satisfied with the course and content is of very good quality and the lab sessions are excellent too!

Great Specialization. I thank the whole team of IBM and Coursera for providing me this valuable knowledge. This specialization is my first stepping stone towards my aim of becoming a Data Scientist.

Also, I would love to convey thanks to Coursera for this wonderful Financial aid program, only because of which I completed this course.

This was by far the best course of the Applied Data Science specialization. It took a lot of time and effort, but it was extremely hands-on and instructors gave you enough guidance to get the project done. I've been using python for more than 2 years, and I don't believe I could've passed this without that experience.

What a fantastic learning experience! This course series has been an amazing journey and I'm proud to say I finally learned Python (and data science) after years of being afraid of programming. This course series has opened many new possibilities for me and I highly recommend it to anyone curious about data science!

The capstone project lets the learner to apply their Data Science skills learned through out the course. All the assignments are peer graded. It is good in one sense, however periodical review from the course admins might make the course grades more authentic and not left to the mercy of the peer reviewers.

It's a high technical course includes new professional and market need tools. In addition to that it review the previous courses tools and used to build our final capstone project.

Thank you, IBM, Thank you, Coursera, Thank you, all Instructors and students who participate in the discussion of courses forum.