SPRING SEMESTER: MATHEMATICAL TOOLS FOR DATA SCIENCE
The Application for the 2020 Spring Semester in Mathematical Tools for Data Science is NOW OPEN!
Handling, processing, and analyzing voluminous and complex data are now incredibly common tasks that influence many aspects of our everyday life. Thanks to the advent of powerful data collection and storage devices in recent decades, the world is all-connected. Geographical, social and cultural preferences, and transportation data, to name just a few examples, are being increasingly used to inform decision-making processes, to discover interesting relationships between variables, or to predict future trends. Major industries and government institutions are now forming data science teams to undertake these challenges.
The scientific and technical issues used to address the above-mentioned topic are complex and highly multidisciplinary in nature. In particular, mathematicians are called upon to prescribe, interpret and supervise quantitative methods of analysis and their corresponding computer implementations.
The goal of this semester is to provide students with a solid and rigorous understanding of the subject’s core. The study of data science with a truly multi‑disciplinary and sound approach necessarily involves strong interaction between statistics, mathematical modeling, pure mathematics and computer science. Students will be exposed to concepts and terminology from data science, preparing them to communicate with and take part in data science teams. In addition, they will learn the fundamental theoretical bases of quantitative methods, statistical models, and computer science, equipping them with the ability to choose relevant and efficient algorithmic solutions for solving problems in data science and mathematical modeling.
|WHY STUDY MATHEMATICAL TOOLS FOR DATA SCIENCE IN GUANAJUATO?|
The aim of this semester is to learn and master the mathematical and computational foundations necessary for students to deepen their knowledge and practical skills in areas related to data science. The aim is that, by the end of the semester, students should:
Successful applicants will:
Click on the tiles below to see details of each of the programs in the course*
*Minimum course load = four per semester
Extra: Workshop on computational tools for data science [2 weeks]
- Introduction to programming in Python: variables, conditionals, loops, functions, introduction to classes
- Introduction to programming in R
- Introduction to SageMath