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
Very good capstone project. Learnt lot of insights on how to represent data through out this course.\n\nVery good starting point for ""Data Science" field. I would definitely recommend this course.
By Julien P•
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.
By Yibing S•
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.
By Ian C•
Felt a bit constrained by the requirement to include the Foursquare API.
By Nikolay D•
Very easy to understand and remember this material
By Hadi N•
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
By Yechen H•
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.
By Ruiping W•
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.
By Pawel P•
Some things were outdated and did not work properly for me.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.
By Alex Y•
Did not like Foursquare and was obliged to use it to complete the course
By Martin V•
As much as I would like to recommend this course, I was really disappointed by the poor quality of the videos in this lecture. They contained a lot of spelling mistakes and were not aligned with what you find in the corresponding notebooks which made it very cumbersome to take notes while watching the lectures. Also the capstone project, while being interesting and challenging, was not properly motivated by the course itself.
I think the extend was good and concept fine but it needs a lot of fine-tuning to be an outstanding course which wants you to continue an do the next one immediately after.
the idea and all that was great, but despite doing all the previous courses, it was very difficult for me to do the project ... I felt I had many cheese holes and got stuck many times ... note, I had no experience with DS, programming before, but coming from a finance background ... I would say the entire specialisation is not for a true beginner ... but the course package overall is very strong I think
By Stefan A•
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).
By Sobhan A•
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 Elvijs M•
On one hand there is some encouragement to experiment and come up with an interesting problem and I actually took some time to come up with something non-trivial before starting. But practically, there is no need to -- you can just take the example notebook from one of the prior weeks and change the city. The evaluation doesn't really reward you for doing something original or extra.
Sadly, the certificate of the specialization as a whole is worthless.
By Izabela K•
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.
By PD T•
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.
By Lindsey L•
The project was a really good way for me to work on my skills. I rated this course 1* because the instruction was abysmal. Too many instances where additional steps needed to be taken to submit a project which were not included in the instructions. Had to rely on comments from students in the forums to learn what I needed to do. I still don't know how to link a Jupyter Notebook to GitHub. Too many times students projects could not be reviewed because the platform did not allow them to submit a shareable link. I could go on, but after sucking way too many hours of my time trying to complete and submit projects because of the lack of complete information in the course, this course doesn't deserve that much of my time.
By Deleted A•
This course's content is out of date. Students have to rely on the posts of other students to work around issues with the course. This is a real shame as the other courses required to receive the certification are well maintained.
By mustansir D•
This course is full of bugs (outdated) and lack of explanation for certain matter is seen in Discussion Forums.
By Paul A•
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.
By Oritseweyinmi H A•
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.
By Aécio A T L•
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.
By Anthony S•
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.
By Marceline C M•
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.
By Srinivas M B•
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.