FAQs

The main objective of this course is to offer professional Masters students a combination of industry mentorship and hands-on data science training. It aims to provide students with practical experience on significant projects beyond the typical classroom setting.

 Students collaborate in teams of 3-4 individuals. These teams work on innovative research projects that are proposed by industry partners.

Each team will receive guidance from an industry mentor, an additional Ph.D. student mentor, TAs, and the course instructor.

Collaborating with industry partners provides numerous advantages. These include access to rich, industry-scale data, insights into real-world challenges, and the opportunity to forge valuable industry connections that can be beneficial for future endeavors.

Students enrolled in the CICS MS program will receive a course announcement email in the Fall semester. Please fill the application form linked within.

Enrollment in the CICS Professional Masters program; by the end of the previous semester have completed at least two of the Data Science core requirements; a grade point average of 3.0 or higher. In rare cases, extremely strong candidates who have less than two data science core courses may be enrolled.

We take a holistic approach to evaluating applications, focusing on the following three main aspects:

1. Coursework: Applicants are required to have completed a minimum of two courses that satisfy the data science concentration core requirements. Many successful candidates have completed three or more courses relevant to machine learning, particularly at the 600-level, which are given preferential consideration. A minimum GPA of 3.0 is required. Historically, admitted students have typically had GPAs exceeding 3.7.

2. Project experiences: We encourage applicants to describe their relevant project experiences and what they have learned from those experiences. Course projects are considered relevant. Many applicants also have additional experiences working on research projects outside the classrooms, such as in research labs, independent study projects, or industry roles. In the answers, we look for characteristics that prepare students to succeed in the course. The following is a non-exhaustive list of valued signals:

   • Demonstration of the student's in-depth understanding of relevant subject knowledge and comprehension of necessary engineering skills in previous projects.

   • Demonstration of research skills in previous projects, such as, conducting a literature review, identifying a problem, collecting suitable data, developing a novel methodology, designing and implementing experiments, and/or presenting the results to stakeholders through a report, presentation, or paper.

   • Demonstration of initiatives and ownership of the projects.

3. Behavioral questions: We encourage students to share their stories and thoughts about communication, teamwork, and time management.

The enrollment is very competitive and the program cannot accommodate many qualified candidates.

Once the above details are sorted out, each applicant will receive an email with the results of the selection process in the first week of December.

• Selected students will have 3 days upon receiving the announcement email to accept or decline the offer. Please watch out for the email. Confirmed students will be enrolled by the college. We request you to drop any excessively enrolled courses so that the students on the waitlists of those courses can be enrolled.

• Waitlisted students have the choice to confirm their intent to stay on or leave the waitlist. If a selected student decides to pursue an alternative plan, a confirmed waitlisted student will be notified.

• International students in their final semester need to be in a class that meets in a classroom. This is because a student visa is given to students who must be in the US, taking classes physically at US university, and in US classrooms.  If a student is taking only one class, and that class does not meet in person, there is no need for a student visa, and the visa can be cancelled. If a student's visa is cancelled, they lose the ability to apply for OPT and remain in the US.

• MS Advising FAQ: IPO and CICS STRONGLY encourage international MS students in the final semester as a residential student to take AT LEAST ONE CLASS, even a 1 credit class, that meets in person. Independent studies DO NOT require you to be in person. Therefore, if you are taking COMPSCI 696DS as your only class in Spring, we STRONGLY encourage you to take ANOTHER class that meets in person. This is a visa rule, not a UMass and CICS rule.

Students who are selected to enroll in the course will receive the project preference form around early January.

The process is structured to ensure that students are matched with projects that align with their preferences. Here’s a simplified overview:

Collecting Project Preferences

• The students who are enrolled in the course receive a project preference form and project descriptions. Students indicate their preferences by scoring each project on a scale of 1 (low preference) to 5 (high preference), and students are encouraged to provide scores for as many projects as possible to optimize matching.

Matching

• An algorithm called fair matching uses students' preference scores for an initial automated matching process. The algorithm tries to satisfy as many students as possible, assigning them projects where they scored 3 or higher.

• Manual adjustment will be made when the algorithm fails to satisfy hard constraints.

• The complexity of the matching process means that accommodating special requests may not always be feasible. 

• Students will be informed about their respective project assignments before the course commences. 

During the weekly class sessions, students will receive professional development education, training in data science software infrastructure, presentations on data science research, and career guidance.

No.