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Data Science Capstone
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Financial aid available
About this Course
The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, and academic partners.
Could your company benefit from training employees on in-demand skills?
What you will learn
Create a useful data product for the public
Apply your exploratory data analysis skills
Build an efficient and accurate prediction model
Produce a presentation deck to showcase your findings
Skills you will gain
- Data Science
- Machine Learning
- R Programming
- Natural Language Processing
Jeff Leek, PhD
Roger D. Peng, PhD
Brian Caffo, PhD
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
See how employees at top companies are mastering in-demand skills
Syllabus - What you will learn from this course
Overview, understanding the problem, and getting the data.
This week, we introduce the project so you can get a clear grip on the problem at hand and begin working with the dataset.
Exploratory Data Analysis and Modeling
This week, we move on to the next tasks, exploratory data analysis and modeling. You'll also submit your milestone report and review submissions from your classmates.
This week, you'll build and evaluate your prediction model. The goal is to make your model efficient and accurate.
This week's goal is to improve the predictive accuracy while reducing computational runtime and model complexity.
This week, you'll work on developing the first component of your final project, your data product.
This week, you'll work on developing the second component of your final project, a slide deck to accompany your data product.
Final Project Submission and Evaluation
This week, you'll submit your final project and review the work of your classmates.
- 5 stars 69.52%
- 4 stars 20.80%
- 3 stars 5.20%
- 2 stars 2.39%
- 1 star 2.06%
TOP REVIEWS FROM DATA SCIENCE CAPSTONE
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!
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.
I appreciate all the work they put into creating the course,. However, it can be frustrating to follow. It would be nice if they would structure it in a more organized fashion.
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.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
More questions? Visit the Learner Help Center .
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In-person, blended, and online courses, data science: capstone.
- Professional Certificate in Data Science
- Data Analysis
- Data Visualization
Harvard T.H. Chan School of Public Health
What you'll learn.
- How to apply the knowledge base and skills learned throughout the series to a real-world problem
- Independently work on a data analysis project
To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.
Unlike the rest of our Professional Certificate Program in Data Science, in this course, you will receive much less guidance from the instructors. When you complete the project you will have a data product to show off to potential employers or educational programs, a strong indicator of your expertise in the field of data science.
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M.S. in Data Science students are required to complete a capstone project. Capstone projects challenge students to acquire and analyze data to solve real-world problems. Project teams consist of two to four students and a faculty advisor. Teams select their capstone project at the beginning of the year and work on the project over the course of two semesters.
Most projects are sponsored by an organization—academic, commercial, non-profit, and government—seeking valuable recommendations to address strategic and operational issues. Depending on the needs of the sponsor, teams may develop web-based applications that can support ongoing decision-making. The capstone project concludes with a paper and presentation.
- Synthesizing the concepts you have learned throughout the program in various courses (this requires that the question posed by the project be complex enough to require the application of appropriate analytical approaches learned in the program and that the available data be of sufficient size to qualify as ‘big’)
- Experience working with ‘raw’ data exposing you to the data pipeline process you are likely to encounter in the ‘real world’
- Demonstrating oral and written communication skills through a formal paper and presentation of project outcomes
- Acquisition of team building skills on a long-term, complex, data science project
Capstone projects have been sponsors by a variety of organizations and industries, including: Capital One, City of Charlottesville, Deloitte Consulting LLP, Metropolitan Museum of Art, MITRE Corporation, a multinational banking firm, The Public Library of Science, S&P Global Market Intelligence, UVA Brain Institute, UVA Center for Diabetes Technology, UVA Health System, U.S. Army Research Laboratory, Virginia Department of Health, Virginia Department of Motor Vehicles, Virginia Office of the Governor, Wikipedia, and more.
Sponsor a Capstone Project
View previous examples of capstone projects and check out answers to frequently asked questions.
What does the process look like?
- The School of Data Science periodically puts out a Call for Proposals . Prospective project sponsors submit official proposals, vetted by the SDS Associate Director for Research Development .
- Sponsors present their projects to students at “Pitch Day” near the start of the Fall term, where students have the opportunity to ask questions.
- Students individually rank their top project choices. An algorithm sorts students into capstone groups of approximately 3 to 4 students per group.
- Each group is assigned a faculty mentor, who will meet groups each week in a seminar-style format.
What is the seminar approach to mentoring capstones?
We utilize a seminar approach to managing capstones to provide faculty mentorship and streamlined logistics. This approach involves one mentor supervising three to four loosely related projects and meeting with these groups on a regular basis. Project teams often encounter similar roadblocks and issues so meeting together to share information and report on progress toward key milestones is highly beneficial.
Do all capstone projects have sponsors?
Not necessarily. Generally, each group works with a sponsor from outside the School of Data Science. Some sponsors are corporations, some are from nonprofit and governmental organizations, and some are from in other departments at UVA.
Why do we have to work in groups?
Because data science is a team sport!
All capstone projects are completed by group work. While this requires additional coordination , this collaborative component of the program reflects the way companies expect their employees to work. Building this skill is one of our core learning objectives for the program.
I didn’t get my first choice of capstone project from the algorithm matching. What can I do?
Remember that the point of the capstone projects isn’t the subject matter; it’s the data science. Professional data scientists may find themselves in positions in which they work on topics assigned to them, but they use methods they enjoy and still learn much through the process. That said, there are many ways to tackle a subject, and we are more than happy to work with you to find an approach to the work that most aligns with your interests.
Can I work on a project for my current employer?
Each spring, we put forward a public call for capstone projects. You are encouraged to share this call widely with your community, including your employer, non-profit organizations, or any entity that might have a big data problem that we can help solve. As a reminder, capstone projects are group projects so the project would require sufficient student interest after ‘pitch day’. In addition, you (the student) cannot serve as the project sponsor (someone else within your employer organization must serve in that capacity).
If my project doesn’t have a corporate sponsor, am I losing out on a career opportunity?
The capstone project will provide you with the opportunity to do relevant, high-quality work which can be included on a resume and discussed during job interviews. The project paper and your code on Github will provide more career opportunities than the sponsor of the project. Although it does happen from time to time, it is rare that capstones lead to a direct job offer with the capstone sponsor's company. Capstone projects are just one networking opportunity available to you in the program.
Capstone Project Reflections From Alumni
“Capstone projects are opportunities for you to deliver valuable, quantifiable results that you can use as a testimony of your long-term project success to the company you work for and other companies in future interviews.” — Gabriel Rushin, MSDS 2017, Procter & Gamble, Senior Machine Learning Engineer Manager
“For my capstone project, I worked to develop a clustering model to assess biogeographic ancestry, using DNA profiles. I felt like I was finally doing real-world data science and loved working with such an important organization as the Department of Defense.” — Colleen Callahan, Online MSDS 2021, Associate Research Analyst, CNA (Arlington, Virginia)
Capstone Project Reflections From Sponsors
“For us, the level of expertise, and special expertise, of the capstone students gives us ‘extra legs’ and an extra push to move a project forward. The team was asked to provide a replicable prototype air quality sensor that connected to the Cville Things Network, a free and community supported IoT network in Charlottesville. Their final product was a fantastic example that included clear circuit diagrams for replication by citizen scientists.” — Lucas Ames, Founder, Smart Cville
“Working with students on an exploratory project allowed us to focus on the data part of the problem rather than the business part, while testing with little risk. If our hypothesis falls flat, we gain valuable information; if it is validated or exceeded, we gain valuable information and are a few steps closer to a new product offering than when we started.” — Ellen Loeshelle, Senior Director of Product Management, Clarabridge
MSDS Capstone Projects Give Students Exposure to Industry While in Academia
Master's Students' Capstone Presentations
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About this Course. The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, and academic partners.
Course description. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series.
Since there was a lot of content, I’ll conclude with my top three tips for doing a great data science capstone project: Choose a good data set: a small, uninteresting, or otherwise hard-to-analyze data set will make it substantially harder to make a great project.
Capstone projects show your readiness for using data science in real life, and are ideally something you can add to your resume, show to employers, or even use to start a career. I find data...
Capstone projects challenge students to acquire and analyze data to solve real-world problems. Project teams consist of two to four students and a faculty advisor. Teams select their capstone project at the beginning of the year and …
Data Science Projects To Try. Whether you’re a complete beginner or one with advanced skills, you can gain hands-on experience by trying out projects on your own or working with peers. To help you get started, we’ve curated a list of the top 15 interesting data science projects to try. See what catches your fancy and get started!
This spring semester the Data Science team at WeightWatchers welcomed back a group of Business Analytics Masters students from Columbia University to participate in two capstone projects. WW ...