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

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.

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

To much focus on the use of the Foursquare API, which is outdated is bit. Other techniques learned in the program are not used, only clustering with K-means. On the other hand, you are forced to experience hands-on reality, when things are just working different then expected (which is meant to be possitive feebback). Week 4 and 5 take a lot of time (far over expected 30 hours, more like 60-80).

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.

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.

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.

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!.

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.

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!

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.

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.

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.

Excellent chance to push in every concept learnt so far. Best thing about the course is the chance to self identify a problem and find the solutions all by ourselves. Great Content. Thanks !

This course is instructive and challenging at the same time. Now I do wish I know a bit more about python and pandas before I jump in this course. But in the end I managed to get through.

Thank You for such a great end to end project, learnt a lot !! Presentation was damn lengthy though

Felt a bit constrained by the requirement to include the Foursquare API.

Very easy to understand and remember this material

I would have liked to come up with a capstone project which did not encourage me to use location data from Foursquare, and rather use other data to come up with problems and solutions which do not necessarily have to do with location data. But all in all, it was an interesting course and great knowledge was gained

Some things need to be updated. Such and such is "Deprecated" errors, typo errors, and less and less thought put on in designing the exercises. I can feel the preparers dropping the ball towards the end of this specialization. Current visualization trends should be included like Tableau.

Overall, the course is very practical, you have the chance to do a project use the technology you have learned so far, and get a feeling of what Data Science work looks like. Recommend for those who interested in Data Science Area.

This project is beneficial by providing the chance to explore Foursquare API and generate some realistic results. However the discussion forum is not well used, questions posted there are rarely answered by teach staff.

Some things were outdated and did not work properly for me.

Peer-graded assignments where one has to create a github repository is totally unnecessary.

The assignments are either correct or incorrect and the scores are depends on your classmates grade to you.

Did not like Foursquare and was obliged to use it to complete the course