Interested in our mini tutorials, June 26-29, 2017?
The CDIPS Data Science Workshop is a three-week student/postdoc-organized program during the summer, where small teams of graduate students and postdocs are paired with mentors from industry to analyze an outstanding problem in data science. The workshop is completely free of charge. It was developed to address an issue that was highlighted by a number of our guests from the Speaker Series: “The gap between academic science and industry is often narrow but deep. Many of the skills you may lack are seen as necessary by an employer, but can be easily learned.”
The workshop aims to provide participants with 3 things:
- Familiarity with common practices and concepts in data science
- A concrete experience to show employers
- Contacts in data science
Who participates in the Data Science Workshop?
Our workshop is for Berkeley/LBNL graduate students, postdocs, and visiting scholars considering careers in data science. We believe that all benefit from hands-on experience in appropriate environments to make informed career decisions. We expect you to have some programming experience, though you don’t have to be an expert just yet! Most of our events are in the evenings so that you can still do your research while you participate in the workshop, though we do encourage you to hack at your project during the day.
Each team will be assigned a mentor. Mentors are data scientists who will guide students towards completing their project. Moreover, we expect participants to use mentors for more than just answering occasional questions or providing technical help. We want students to establish with mentors a relationship of learning, dialogue, and advisement. If you are a mentor, click here for more information.
What do people work on?
There are two types of projects that a team can work on:
- A project proposed by their mentor.
- A Kaggle project.
We will be hosting an information session for applicants on April 5, 2017 at 4pm at the Berkeley Institute for Data Science (190 Doe Library).