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Pre MSc AI/Data Science

Senior year BSc for MSc AI/DS
Scientific training in data science

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Pre MSc 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.

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MSc in AI/DS (2 Year)

at a glance

HIGH QUALITY ONLINE CLASSES

ONLINE TA SESSIONS

12 COURSES & 1 DISSERTATION

8 WEEKS PER COURSE

2 COURSES PER WEEK

1 YEAR PROGRAM

Learning Outcomes

APPLICATION OF ABSTRACT MATHEMATICAL CONCEPTS TO REAL WORLD PROBLEMS

MATHEMATICAL AND BAYESIAN STATISTICS, DYNAMIC OPTIMIZATION FOR UPPER LEVEL STUDY

MSC-Tabs

Tuition Fees
Tuition Fees
  • Application fee : CHF 200.- (Non-refundable)
  • Administration fee : CHF 1,000.- (Non-refundable)
  • Courses : CHF 1,650 per course
    – 2 courses per term (Bi-monthly payment)
    – 1 course for 5 ECTS*

Advance to MSc requirements

  • Coursework – 60 ECTS* wth average 60% or above
  • STA511 and STA512 - Average 60% or above

*ECTS – European Credit Transfer and Accumulation System

Admission
Admission

Class module : Online only

Credit : 60 ECTS / (Level / EQF 7)

Required documents 

  • Bachelor diploma and transcript (mandatory)
  • Graduate school diploma and transcript (if applicable)
  • Statement of Purpose
Admission Examination
Admission Examination
  • No official admission examination
  • Following documents will be thoroughly reviewed
    • Statement of Purpose
    • Undergraduate transcript

 

Please note that if you have not done any STEM education during your undergraduate or even in graduate studies, we recommend you to try MBA AI programs' business track. Even if you have applied for PreMSc, if no record of mathematical training is found, the offer letter will be given to MBA programs.

Course Curriculum
Course Curriculum

1 Year for 12 courses
1 Term for 8 weeks with 2 courses

Prep classes are available

  • LaTeX for assignments and paper writing
  • Programming prep for Python

Core Course Description

Program Structure
How classes work
  • 3-hour Video-recorded classes per week (Required)
  • 1-hour support sessions per week  (Selective)
  • Final exam / term paper 1-week after the end of the course
  • Total 12 courses, 2 courses for 1 term
  • 1 term for 8 weeks
English requirement
For non-native English speakers, should meet one of the following criteria

For non-native English speakers, should meet one of the following criteria by graduation

  • High school or University level diploma from an all-English program
  • TOEFL iBT 100/120 or above (with each section at least 21/30)
  • IELTS 7 or above (with each section at least 6.5/9)
  • Pass grade from SIAI’s internal English course

 

Internal English course

  • Course fee: CHF800
  • Course schedule
    • July~Aug (8 weeks)
    • Live session
    • 3 hours per week (usually weekend)

Q&A

Teaching assistants (TAs) assigned to each course solve problem sets, which are guidelines for every assignments. If a student find it difficult to follow the courses, first it is recommended to reach out to TAs, and together with the instructor, SIAI provides a possible solution. We also provide mentors whose performance in previous year is outstanding in that course.
Teaching assistants (TAs) assigned to each course solve problem sets, which are guidelines for every assignments. If a student find it difficult to follow the courses, first it is recommended to reach out to TAs, and together with the instructor, SIAI provides a possible solution. We also provide mentors whose performance in previous year is outstanding in that course.
Computer programming indeed is essential in every sub-discipline at SIAI, but students are given ample amount of study materials. For starters, Issues in Computer Programming (OPT101) , a short prep course given to all incoming students, covers a number of programming issues that are basics for later courses. In addition to that, for every problem set and term paper, a set of guideline code lines are given so as to provide right direction.
Unfortunately, as an online business school, we do not provide any offline support for learning. However, students are free to ask for mentors for each course. Mentors are chosen by the course’s instructor by various factors such as class record, friendliness, other course performances.
Teaching assistants (TAs) assigned to each course solve problem sets, which are guidelines for every assignments. If a student find it difficult to follow the courses, first it is recommended to reach out to TAs, and together with the instructor, SIAI provides a possible solution. We also provide mentors whose performance in previous year is outstanding in that course.
Teaching assistants (TAs) assigned to each course solve problem sets, which are guidelines for every assignments. If a student find it difficult to follow the courses, first it is recommended to reach out to TAs, and together with the instructor, SIAI provides a possible solution. We also provide mentors whose performance in previous year is outstanding in that course.
Computer programming indeed is essential in every sub-discipline at SIAI, but students are given ample amount of study materials. For starters, Issues in Computer Programming (OPT101) , a short prep course given to all incoming students, covers a number of programming issues that are basics for later courses. In addition to that, for every problem set and term paper, a set of guideline code lines are given so as to provide right direction.
Unfortunately, as an online business school, we do not provide any offline support for learning. However, students are free to ask for mentors for each course. Mentors are chosen by the course’s instructor by various factors such as class record, friendliness, other course performances.

SIAI Experience Stories 

Review

Sungsu Han (MBA AI/BigData, Class of 2024)

Previous school: BS in Electronic Engineering, KyungHee University

I took it while working at the company and taking SIAI school classes in parallel.
It was a near-death schedule that put me through a hard time, and it taught me a lot.
One of my favorite stories says: Go beyond your limits. I was able to gain that experience while working at a company and attending SIAI.
I learned that I can achieve greater growth when I push myself to my breaking point.
Many SIAI students besides me are having similar experiences.
It has been a great asset in my life to be able to meet friends with majors in various fields with whom I can share suffering and grow together as school colleagues, teachers, and friends.
I am currently enrolled in SIAI MBA AI/BigData and am about to graduate.
While writing my graduation thesis, I learned through SIAI's educational philosophy how to find solutions that only I can create to solve problems.

Pre-MSc in AI/DS

Pre-MSc AI/DS can function as a top-up masters program for students with gaps in academic pursuits. The program provides one-step above the usual undergraduate level scientific training in mathematical statistics, computational statistics, and scientific modeling.

Target students are

  • MSc AI/DS applicants with less sophisticated math and stat
  • Prospective graduate students in gap year
  • Wannabe data scientists without deep math and stat background

Admission conditions are

  • 60% or above in average GPA in coursework
  • 60% or above in STA511 and STA512
A first step for advanced studies in science
Reach your new height in data science and be the leader in the field
Course Curriculum
Department Contact Info

Master of Science Program

[email protected]

Mon – Fri 9:00 A.M. – 6:00 P.M.

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