Capstone did provide a true test of Data Analytics skills. Its like a being left alone in a jungle to survive for a month. Either you succumb to nature or come out alive with a smile and confidence.
Wow i finally managed to finish the specialization!! definitely learned a lot and also found out difficulties in building predictors by trying to balancing speed, accuracy and memory constraints!!!
교육 기관: Lucas•
In this last module I have learned a lot. It was demanding and quite tricky as you were asked to take your own decisions as there is no best answer at all. I learned to decide what I want and to create an appropriate solution. The best lesson so far along this specialization track.
교육 기관: Nirav D•
I loved doing the capstone project for the Data Science specialisation. I applied all the skills I learnt during the length of the specialisation on Coursera. Having completed this project, I feel more confident about my skills as a data scientist in solving real world problems.
교육 기관: Nobumasa•
This capstone requires all the skills that you learned from the series of specialization in addition to self-learning about Natural Language Processing. So, it was challenging course to me, but if you go through it, you can find yourself armed with the data scientist skill sets.
교육 기관: Alma S•
Really challenging but satisfying enough!
Thank you for Cousera team who patiently developed such a beautiful program for upskilling us, the so-called data scientist! :)
The journey to accomplish this Data Science Capstone is something I'd remember & cherish, indeed.
교육 기관: Perry B•
Awesome specialization! Super happy to be done with 100% on all the courses and 95% on the capstone. I would love to be a part of this great team, maybe as a mentor. Thank you to all the instructors for great lectures and to mentors who helped with the forums.
교육 기관: Akthem R•
A very stimulating and challenging capstone. It is stretching and puts all the 9 specialization courses material to use. It also gives the student a glimpse of what Data Science in real life is and touches on Natural Language Processing as part of AI.
교육 기관: Shreeram I•
The sequence of activities in execution of the project envisages multiple interactions with your peers and unfolds your creative aspect to churn out a solution to put all the learning into practice!
Cheers, DSS team - Brian, Jeff and Roger 😁
교육 기관: Javier A D•
It was a new world for me. To hard trying to dive in the subject. But the bases and the effort to research in literature and in the foros let me develop a model of a beginner but with great knowledge to apply in new developments in my work.
교육 기관: Hathairat W•
The assignment was designed very well. I struggled and was thinking of giving up. I'm glad I didn't. The assignment actually required all skills I learnt previously. A bit time consuming but achievable. Thank you very much!
교육 기관: Scott W•
Was a great course. There was no hand holding, this is the capstone so it was time to put everything to use on a problem that wasn't outlined for you and required you to self study and work with others to deliver.
교육 기관: Samuel Q•
Great way to end the specialization because it forces students to think on their own and be resourceful. It is a totally different type of analysis than on any previous course so it was a great learning experience
교육 기관: Ivan C•
Amazing project! At first glanse It looks strange, but de facto it's standart data science problem: you should analyze raw data, clean it, build some models and make data product. I highly recommend this capstone.
교육 기관: Luis E B•
Excellent to start in data science. Nothing learned deeply but you understand how you can improve. Now I can improve by my own or choose other courses based on my experience, interest and capabilities.
교육 기관: Maxim S•
Thanks for this competitive task! For me the text processing seems to be the most interesting part of data science. I believe, this knowledge will help in my future projects. Johns Hopkins is the best!
교육 기관: Max M•
Hard but very rewarding. Unless you really have already programming experience it highly likely that it will take you more than one try to complete it.
Really enjoyed it. Very challenging.
교육 기관: Julia P•
This class was a huge challenge for me, but it pushed me to learn a whole lot and practice many of the skills that I had learned in previous courses! I had a lot of fun, too. Thanks!
교육 기관: Phil F•
Well-paced, highly structured Capstone that allowed me to put to the test the skills I honed during the 9 previous courses in the JHU Data Science specialization. Strongly recommended.
교육 기관: Keidzh S•
Brilliant course, the final chapter for the data science specialization. Spent lot of time making my final project, but it wirth it. Glad that I found this specialization a year ago.
교육 기관: Daniel V•
The best part is the surprise of something totally new like NLP and the fact that you have to figure it out by yourself and then apply the theory. Guess what... just like real live.
교육 기관: Lam C V D•
Course capstone is too tough for beginners. Requires Natural Language Processing knowledge in advance. Also the method used is outdated already since it was launched 4 years ago.
교육 기관: cesar a f n•
Incredible course and program, thanks for this. I decided to do a master in data science. I am mathematician an with all the algorithms and IA, i feel that it´s perfect to me.
교육 기관: Roberto D•
This course was very challenging. It resembled a real world task, where an idea is presented and it is up to the user to research methods and processes for the best outcome.
교육 기관: Dimitrios G•
It has been a great experience. There is a big problem though, in the way the final project is being evaluated. Way too subjective questions, providing non definite grades.
교육 기관: Vivek S•
Could improve on detailing the material , adding more technical stuff, but then again data science is very vast and it is best i the students explore things on their own
교육 기관: Pierre B•
Great course, I learned a great deal about data science. The course is well structured and provide a great overview of the requirement and possibilities of data science.