Pre MSc AI/DS Program Intro
Welcome to the introduction of SIAI's lecture notes for PreMSc AI/Data Sciencee Program.
Program Intro
PreMSc in Artificial Intelligence / Data Science – Pre MSc AI/DS is a step-up program for students whose undergraduate study has not provided sufficient background for MSc AI/Data Science. The track provides junior to senior year undergraduate studies in BSc that are shared with MBA AI students. Qualified students are eligible for the MSc AI/Data Science program.
Although most courses are jointly provided with MBA AI's technical track, two final courses testing mathematical extension of asymptotic property will be a determinant if the student is eligible to MSc AI/Data Science. In addition, average GPA must be over 60%. If unsuccessful, students will be given choices between switching to MBA's tech track and termination.
University majors with highly correlated curriculum are Statistics, Mathematics, Physics, Industrial Engineering, and Economics. For other majors, prospective students are recommended to check similarity in academic training with SIAI’s prep class for math & stat basic training.
Admission examination
There is no admission examination for this pre-training program, but we recommend students carefully go through open lecture materials for MBA AI.
Most incoming students think they are well qualfied for MSc AI/Data Science, but often, it turns out that they are not even able to do the first problem set assignment in MBA's first course, STA501: Data-based Decision Making.
The admission committee issues warnings to the students, and mostly recommend to do MBA AI's business track, instead of technical track. For the difference, please take a look at the MBA program introduction on SIAI's homepage.
Although the school is open for the first quarter for STA501: Data-based Decision Making and STA502: Math & Stat for MBA I, students earned below 50% in examinations will not be admitted to PreMSc AI/Data Science and AI MBA's technical track.
Graduation requirement
The program is consisted of total 12 courses, each carrying 5 ECTS. Successful students have to earn 60% or above in the final two courses, STA511 and STA512, and pass grades from all other courses. The school allows additional 12 months of extension to successfuly finish the coursework requirements. Minimum pass grade for each course is 50% or C- in letter grade. Students with lower than 50% must re-take the course in the following year.
Although the school committee may allow students to advance to MSc AI/Data Science, if one of the course grades is below 50%, on the condition that student re-take the missing credit, but STA511 and STA512 grades must be over 60% to be eligible for the temporary waiver.
If more than 3 course grades are below 50%, the committee is not allowed to offer any temporary waiver.
Please note that there is no diploma certificate issued in this program.