Collaborators
This page contains information for collaborators interested in working with students in Data Science at Olin College.
Do you have data? Do you have questions? Would you like a student team to help?
Starting in March 2016, students in my Data Science class will be looking for external groups to collaborate with. You might be interested in working with us if:
You have real-world data you can share with a small group of students (or there is freely-available data you would like them to explore).
You would like help with exploratory data analysis and visualization.
You are willing to interact with the team at least a few times over the course of the semester to help them get started with the data, to tell them about questions you are interested in, and to review their preliminary findings and provide feedback and suggestions.
What kind of work can the students do?
Students in this class are engineering undergraduates with Python programming skills. They will be learning a practical set of tools they can use to turn data into useful knowledge.
They will work in teams of 2-3 students. Projects that would be a good match for this class might include:
Projects that require data cleaning and transformation, or merging data from several sources.
Open-ended questions and exploratory analysis.
Custom visualizations, and possibly interactive visualization tools.
Simulation of systems that change over time, and predictive analysis.
For more specifics, see the Outline of Topics.
Some frequently asked questions
1) What programming languages will the students use?
I expect most projects to be in Python, but some students know other languages. If your project requires another language or a particular tool set, we should talk.
2) Will the students deliver their code along with the final report?
I will encourage students to make their code public, if appropriate, or at least deliver it to the sponsor, in order to make their results replicable. The details might be different for different projects.
Students in this class are familiar with version control systems like Git and Subversion.
3) How much background do the students have in statistics?
Some of them have taken the Statistics AP, but for most this is their first college-level statistics class. They will learn basic methods of exploratory data analysis, estimation, regression, and hypothesis testing. We will also cover some machine-learning tools.
If a project requires students to learn additional methods, they can do that. But projects that require advanced statistical analysis might not be appropriate.
The students have programming skills that might allow them to develop novel analyses and visualizations.
4) Can the students work with confidential data?
Yes. One of the goals of the class is to give students experience dealing with real-world issues like confidentiality. We will discuss the ethics of data management, including privacy and confidentiality, and students will learn methods and tools for protecting data.
If your project requires students to sign an NDA, we can discuss that option.
5) Who owns any intellectual property created by the project?
In general, the students do. At the end of most projects, the students make their analysis and code available to the collaborator without an explicit contract. In some cases the students contract to provide a perpetual license for the use of their analysis and code.
Another option is that the student can make their work available under an open source license.
A little about Olin
Olin College of Engineering is a new undergraduate college founded with the mission to fix engineering education. We have professors who are passionate about teaching, and students who are engaged and excited about learning.
Our curriculum is hands-on and, like this Data Science class, includes many projects where students engage with real-world problems, working with external collaborators.
Olin is in Needham, MA, about 10 miles from Boston.
Project descriptions from 2014 are here, and projects for 2015 are here.