Oct 24, 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
Mar 04, 2020
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.
von Ferenc F P•
Feb 26, 2019
This is really challenging course, especially that you get hint on how to use a RESTful API (of Foursquare), how to create heat maps, or create different marking on a map using folium. The Capstone was really challenging, because you can practice what you have learned during the courses of the specialization, like how to start from the scratch a project, how to apply the data science methodology, like business understanding, gathering, analyzing, and cleaning data (most of your time you will spend on this), applying the right machine learning algorithm to solve the problem (modeling), using Jupyter Notebook on IBM cloud and using github. In the end you should also prepare your final report including the business understanding, describing your data, presenting your result, and placing a discussion section in the end. It took me 4 full days to complete the capstone, but I learned a lot.
von Piyush L•
Oct 21, 2019
This is the best part of the specialization and I learned a lot in this Capstone Project. If you've been doing all of the 8 previous courses, believe me those 8 courses are nothing compared to this course when it comes to putting time and hard work. You will learn a lot of things including web scraping, connecting to a url, using geolocation services to get data about a location. You'll also use foursquare API to get popular venues in a particular location. This project is super interesting but at the same you have to put in a lot of work too! It took me more than a month to do this capstone alone but it can be easily done in around 3 weeks if you're dedicated in completing it.
von Nur C N•
Jul 23, 2019
This course is really good and give enough challenge on the final project, especially on how to get data from multiple sources: scraping data from web, call APIs, and visualize it on map after call the clustering algorithm. I like the way we should prepare all material to complete the course like visual presentation with slide/blog post, report, and share the code in GitHub. Really glad I take all these 9 courses, can't wait to take other specialization course.
von LEOPOLDO S•
Jan 09, 2019
Very Good. This is my first contact with data science with python and associated packages.
In the end of the course I'm able to deal with data using python and a lot of tools that helps the job and let this job more fun.
A very well organized and balanced course with videos and very good material for practical labs.
I have a Swisse Knife with me to deal with future researches on data science.
von Sumit G•
Jan 26, 2020
The course was very helpful in presenting me the world of data science, what exactly are the things we need to be proficient in to excel in this field ! Best course of all was Machine learning with Python, you will enjoy doing it ! and we need more questions in quiz to test what student has gained at every step.
von 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.
von Jamiil T A•
Mar 30, 2019
A must take capstone project. Enroll for it and you will be moved by the project... Very interesting !
von Tara S•
Apr 26, 2020
The assignment is in and of itself nice, but it is too free. I would have liked a more restricted assignment. During the specialization we mostly had to watch how stuff was done, without much practice on our own, so the step to this assignment was quite large, especially if you are graded by your peers. We were also graded on stuff that was not part of the course, such as reports and presentations. I understand that this is important, but not the aim of the course. Furthermore, we were graded by peers, who are the same level. How can they grade a submission if they themselves do not yet know what is good and what is not?
von Armen M•
Dec 08, 2019
Just terrible , No Any Idea what to build no any suggestion what methods to use togeher
von Pablo V V•
Apr 02, 2019
more exercises, more projects.
von Muhammad F S•
May 09, 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.
von James C•
Jul 14, 2019
Good class, very useful. Peer grading is a great idea, don't like the practice of posting notes in the forum with subjects like "You grade mine and I'll grade yours." At the least, it gives the appearance of cheating. It is also wasteful, as it leads to some assignments being graded multiple times while others are waiting in the queue. This is a practice that Coursera encourages, which is baffling to me. Even in the last class in a 9 class series, I ran into people submitting blank or nearly blank assignments, with no content or inappropriate content, who were apparently hoping for a pity pass or cheating.
von Hayford T•
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!.
von 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.
von Dayli S•
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.
von Marvin L•
Oct 31, 2019
It was very good.. Overall. few things I like to add.
Sharing my notebook from Cloud was not working a lots time.
GitHub , or Jupiter Notebook with simple 2 lines of coding did not work..
Also, a lot of time, cloud machine just spins.. -- without showing it
My resource got close to limit , - Could not add more code..
Instructions were out of date, could not be applied current version
Working with Cloud machine was challenging !!
von Julien P•
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.
von Yibing S•
Jul 10, 2019
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.
von Ian C•
Apr 26, 2019
Felt a bit constrained by the requirement to include the Foursquare API.
von Nikolay D•
Dec 27, 2018
Very easy to understand and remember this material
von Hadi N•
Dec 28, 2019
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
von Yechen H•
Oct 06, 2019
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.
von Pawel P•
Nov 05, 2018
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.
von Alex Y•
Aug 09, 2019
Did not like Foursquare and was obliged to use it to complete the course
von Garima K•
Mar 31, 2020
Outdated and poorly taught specialisation. My best experience on Coursera has been Andrew Ng's ML course and maybe it raised the bar too high. But that was a course that taught the student (keyword: taught). This does not even come close. Would not recommend.