I get now (8th of July) a message that I can only begin in August on my assignment although I have finished week 4 succesfully!!!

I find it unacceptable that Coursera tries to let you renew your monthly subscription over and over again.

Could you unlock my assignment week 5 please?

Also Coursera let you use IBM lite subscription for free in the beginning but if you use it a lot, the lite version is not enough. You can upgrade, if you pay...

If you enroll for subcourses, you are charged each time you submit another small part.

the classes itself are good but Coursera is not clear on how much you need to pay in the end. The prices they let you believe seem reasonable but there are hidden extra costs.

Like other courses of this program, it's just worthwhile for someone who is still learning Python, but even in theses cases, there are better course to take. The grading system is the worst I've seen in more than 40 courses at Coursera.

Terrible. I was more than half way through this course and they changed the course and I had to start over. It was already unclear, now the instructions are much less than before. A waste of money.

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.

A tough course! I'm not a 9 to 5 Data Scientist so I need to made a lot of research in order to finish the project. But in the end it deserved it. I've learn a lot of things: technologies, libraries and concepts. Even my current job is PHP Developer I was amayzed how many tools from my current domain activity I can use on Data Science (Git, programming, SQL, Web scraping, Office suite tools). It was a well spent time and looking back on the overall experience for IBM Data Science Professional Certificate my one word conclusion is: "professionalism". And the second word that defines IBM since I hear about it is "innovation".

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 Data Science course helped me learn and practice at my own pace (considering that I am a working Program Manager professional). The cloud environment was little confusing initially but later got a hang of it. Appreciate the faculty for doing a tremendous job to creating the course material and supporting with the process throughout. Thank you again.

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.

THANK YOU IBM AND TO ALL THE INSTRUCTORS OF THIS COURSE.

IT WAS TRULY AN AMAZING EXPERIENCE IN THE FIELD OF AI-EQUIPPED DATA SCIENCE.

THE COURSE HAVE BEEN DEVELOPED VERY PROPERLY WITH PRACTICAL LAB SESSIONS MAKING YOU READY TO ACCEPT PROFESSIONAL CHALLENGES.

ONCE AGAIN KEEP IT UP TEAM IBM.

THANK YOU

I really like the hands-on exercises in this course, very interesting. And the capstone project make me review all skills I've leart in this course. I hope I could become an volunteer TA for this Data Science course and contribute to our learner community. Thank you for providing this course!

I'm glad we get to choose the theme of our final project, because I had a lot of fun, and not having any templates or guides to follow really tests what you have learned until now.

This course can either be really fun or really boring, depending on what YOU choose as your final project.