What is the Data Science Practicum Program at USF?
Introduction
The Master of Science in Data Science (MSDS) program at the University of San Francisco (USF) includes a nine-month practicum (internship) component assigned to each student. The practicum offers an opportunity for students to apply the skills and knowledge they learn in the program to real-world projects and problems. The practicum is an essential part of the MSDS program with partnerships in a variety of industries: technology companies, government agencies, non-profit organizations, universities, research institutions and new start-ups. These partnerships change and grow each year.
Process
Many students think the practicum component is one of the major reasons to choose this program and we understand that new candidates are also interested to know more about practicum. We would like to explain in more detail about the procedure of the practicum, so that you can have a better understanding about the process and what the practicum has to offer. Please consider the timeline and information here are from Cohort 11 so future cohorts might be slightly different.
In September, students receive a digital pitch book which includes around 60 companies’ information, descriptions, and project details. Some companies have multiple projects, and each requires a different skill set. Thus, it is important to read through the pitch book and find the company or project you are interested in. The following week there are three pitch days for all companies to present. Each company will have about five minutes to share their company values, mission, and details about the projects. After the presentation, students have a few minutes to ask questions. You can imagine how informative the pitch days will be, considering a great number of companies are presenting. I suggest taking notes and paying extra attention to the companies that you are interested in!
Then we are required to submit a list of our top 15 companies, and a list of five companies we are interested in the least. Though it can be overwhelming to select which companies you are interested in after being given an enormous information, the MSDS faculty offer many meetings to help us finalize the most suitable choices. We all get a lot of help along the way.
After submitting our lists, the program faculty begin to assign companies to students based on student interest, professionalism, skill sets, and background. Students then receive interview invitations (although not all companies require interviews). The interview process is somewhat less complicated compared to external recruitment and most of them are behavioral only, but a few require technical rounds.
The whole process is complete around mid-October. Students usually start working in November and continue working two days a week until graduation.
What makes practicum special?
First, the practicum involves students working on a project under the guidance of a faculty member and a mentor from the partner organization. Students will get as much help from the MSDS program faculty and the company mentors. Second, the practicums have partnered with companies from different industries. By completing participating in the practicum, students have the opportunity to make connections with professionals in the industry, which can be valuable for networking and job searching after graduation. Third, practicum provides a platform for the students to test their knowledge and skills on real-world problems and projects. This helps to bridge the gap between academia and industry and prepares the students to tackle the real-world challenges with more confidence. Finally, San Francisco is a major technology hub, and while working in San Francisco, you can network with other professionals to potentially gain more opportunities.
How did coursework prepare students for practicum?
Even though we are only halfway through this program, we have been powering through and have taken many useful courses such as Exploratory Data Analysis, Computation for Analytics, SQL, Linear Regression, Data Acquisition, and Machine Learning. Some courses build fundamental knowledge, including statistics, programming language, and data visualization, while other courses help students with advanced understanding in machine learning, data structure, and distributed computing. Moreover, all courses include hands-on projects, which give us the opportunity to apply knowledge in a practical setting, and help students develop the required skills in practicums.
What are our practicums?
Jinwei: I work at KNIME, an open-source data analytics platform that offers no-code/ low-code solutions for data science. I choose to work here for two reasons. First, this software is ground-breaking for data science in that provides opportunities for non-coders to analyze data just like the professionals. Second, the project is an integration of python and KNIME by creating a new node, which seems interesting to me and suitable for my skill sets.
Lanting: I work at the Metropolitan Transportation Commission. MTC is a governmental agency for Bay Area transportation planning. They have worked with USF for years, and have USF alumni working on the data science team as our mentors. They have a variety of projects that cover quite a few interesting topics, such as data engineering, computer vision, and AWS. The company gives freedom and support to students completing the projects.
If you are interested to know more details about the practicum, click the link below:
https://www.usfca.edu/arts-sciences/programs/graduate/data-science/internships
