About Us
SIAI
Background
The true academic name of Artificial Intelligence (AI), often a synonym of Data Science, is Computational Science. The advent of this new academic study has long been pre-dated by the limitations of top-down logic modeling and real-life data based researches. Computational Science relies on mathematical and statistical approaches as was the traditional methodologies, but are also benefited by artificially generated simulation data and multi-patterned big data, both of which traditional model-based approaches fail to leverage full potential of the data sets.
There are a myriad of disqualified coding-only schools with shallow mathematical and statistical understanding for teaching AI. Untold number of engineers claim themselves data scientists with surprisingly limited understanding of mathematical statistics in computational science. SIAI counter-claims that the new approaches must be multi-disciplined ranging from mathematics, statistics, computer science to bio, economics as well as information science. SIAI believes, with all the necessary trainings, we can call ourselves “Data scientists”.
Math & Stat based
Every discipline in quantitative science is based on core methodology of science, which is mathematics and statistics.
SIAI strongly emphasizes the value of applied mathematical and statistical understanding of data science studies, as is for all top-notch institutions in this new field. Applied training incorporates business applications in an abstracted setting, which will be fitted to a variety of real-life situations in every day data science research.
Unlike coding only educations for ML, DL, and RL, SIAI has a motto of “Rerum Cognoscere Causas“, meaning a person knowing causes of things. Our training helps students to understand why every model is built for what purpose, how it is applied, and what are the key cautions in real-life applications.
Scientific Programming
In computational science, abstracted theory meets real world by Scientific Programming.
Dissimilar to software engineering training, data scientific coding is to transform mathematical and statistical understanding into computer works. Such translation can be trained in class exercises, projects, exams, and dissertations. SIAI coding training coverage is ranging from Latex for math writing to Python/R for analyzing, to Tableau/Kibana for data visualization, and to MySQL and Elastic Search for database structuring.
Such programming training will ultimately be applied to real world problem solving, which is the essence of daily data scientists’ and research scientists’ job.
Swiss to Globe
SIAI not only targets to Swiss and European students. As an online school for higher education, SIAI targets to every wannabe data scientists, data analysts, and research scientists in the world.
Guaranteed by Swiss quality education, our supreme quality education is provided mainly in English, but we also support students speaking in Japanese and in Korean for aspiring Asian students by means of extra lecture videos and transcripts.
Thanks to online education platform, our education service is available anywhere in the world. Although quality control is our key in operation, we believe the location and time free education can surely encourage students to dedicate their 100% to learn as much knowledge as possible.
