Industry

Memberships

We have designed four types of initiative memberships for helping companies reach immediate and long term data science and analytics goals. Included with each membership and core to our partnership model is the placement of data science teams (M.S. in Data Science and Analytics) students within your company for up to 7 months as part of their practicum experience. Each of these teams is mentored by a faculty member to help the both the company and the students maximize the practicum experience. Two examples of past projects completed during a practicum scenario are building a natural language driven recommendation system and developing deep learning neural networks for market classification. All memberships provide one of a kind recruitment opportunities and talent development. For more information, please contact Paul Anderson at andersonpe2@cofc.edu.

Recruitment Membership

• Consideration for selection of two-student team (possibly up to four students) for practicum, mentored by a faculty member
• Membership on the joint industrial advisory board with related communications about events

Advanced Recruitment Membership

• Priority selection of two-student team (possibly up to four students) for practicum, mentored by a faculty member
• Priority access to students for full-time hiring opportunities
• Invitations to members-only events to network with faculty, alums, and students

Research Membership

• Priority placement of a two-student team (possibly up to four students) for practicum, mentored by a dedicated faculty member
• Priority access to students for full-time hiring opportunities
• Invitations to member-only events to network with faculty, alums, and students
• Joint industry and academia grant proposals and partnering on research projects

Project Details

The practicum provides students with the opportunity to gain real world experience working with our industry partners. It is a required component of the curriculum, where teams of students work with a practicum company to identify, define, scope, and analyze a relevant data science and analytics problem. All groups are additionally supported and supervised by MS in Data Science and Analytics faculty. Following an initial hypothesis, students typically engage in data acquisition, exploratory data analysis, feature extraction, model development and evaluation, as well as oral and written communication of results. Class schedules are set so that students can work onsite one to two days per week. Students devote 15 hours a week to practicum on average. Projects may be paid or unpaid.