Data Science Capstone
Created by: Jeff Leek
Course Description
Instructor Details
- 4.2 Rating
196 Reviews
Jeff Leek
Jeff Leek is an Assistant Professor of statistics at the Johns Hopkins Bloomberg School of Public Health and co-editor of the Simply Statistics Blog. He received his Ph.D. in statistics from the University of Washington and is recognized for his contributions to genomic data analysis and statistical methods for personalized medicine. His data analyses have helped us understand the molecular mechanisms behind brain development, stem cell self-renewal, and the immune response to major blunt force trauma. His work has appeared in the top scientific and medical journals Nature, Proceedings of the National Academy of Sciences, Genome logy, and PLoS Medicine. He created Data Analysis as a component of the year-long statistical methods core sequence for statistics students at Johns Hopkins. The course has won a teaching excellence award, voted on by the students at Johns Hopkins, every year Dr. Leek has taught the course.
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Reviews
By Patrick C on 26-Sep-19
It was a challegne for me, but also a fun!Very interesting experience in a new promising field!
By Bob C on 20-Sep-19
A capstone is typically defined as integrating key material from a course. This capstone did not require material from key courses, specifically the machine learning, regression models, and statistical inference courses. That was a great shame. Instead, it threw us into a completely new area, Natural Language Processing.
There were many complaints about that, and I agree. However, it was
a challenging task to explore an area in data science we didn't touch
on, and challenging in terms of the
programming and enormous data file sizes. In that sense it was probably
good prep for unexpected challenges in the workplace and therefore good
training to make us real data scientists. Still, I would like to see the capstone rejigged to include material from the missing courses. As for NLP, some students claim it is not a useful area to study, but in my case it is exactly the right thing for me to study as I work with analyzing user queries in the form of tickets in a CRM. I found it especially trying to try to integrate some material such as Kneser-Ney theory and opted for a more basic approach. My learning experience would have been better with some proper instruction in that area.
By Renato O F on 19-Sep-19
Indispensable for those who want to master the R language along with data science. I highly recommend this 10 courses. Believe me you will not regret it.
By Inderjeet S on 19-Sep-19
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!
By Shambhavi S on 8-Sep-19
Feeling proud after completing all the courses under Data Science Specialization. This was not an easy task to complete especially if you are not familiar with the Statistics. Requires continuous dedication and motivation to follow and complete. Course is well designed and cover most of the topics. Its just stats part can be enhanced further to cover some basic aspects. Thanks for all the support
By Pratish B on 8-Sep-19
Very engaging and well-designed course. Many thanks to the instructors and SwiftKey!
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Quality Score
Overall Score : 84 / 100









