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.

  • CIMAT is a research facility with four decades' experience in pluri-disciplinary studies, uniting basic math, statistics and computer science. Our combined approach to these areas makes the perfect setting for the study of Data Science, as the experts in each area will give you the fundamentals to help you to understand data science problems from both a statistical and an algorithmic point of view.
  • At CIMAT, you will discover how nice constructions from basic mathematics areas, such as Geometry and Algebra, may help you in understanding data.
  • CIMAT has an extraordinarily vivid academic environment, with a continuous flow of academic events such as conferences, seminars and congresses dealing with cutting-edge research areas and involving leaders of their fields from the Americas, Europe and Asia.
  • Guanajuato is one of the greatest cities to live in México; an environment where you can be immersed in a colorful, joyous, Mexican atmosphere, learn or practice Spanish and discover the rich culture of México.


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:

  1. master the mathematical foundations of data science; i.e., the most important concepts in discrete mathematics, rigorous proof techniques and multivariate statistics in order to provide sound mathematical models for data science problems;
  2. master the algorithmic foundations of data science (e.g., the basic tools to quantify algorithm complexity) and be able to identify canonical algorithmic problems and propose adequate algorithm paradigms to solve them;
  3. be able to effectively participate in a multi-disciplinary team involving statisticians, mathematicians, computer scientists and specialists from other areas to solve a data science problem as a team;
  4. discover different aspects of the Mexican culture by immersing themselves in one of its most vibrant historical cities in the heartland of Mexico.


Successful applicants will:

  • be currently enrolled in a higher education institution, pursuing a major that includes components involving Mathematics, Statistics, Data Science, or Computer Science.
  • have studied at least one linear algebra course. The student should be familiar with the concepts of vector spaces, bases, dimensions, matrices, linear applications, determinants, and kernels.
  • have studied differential, integral and multivariate calculus courses. The applicant should be familiar with the notions of limits, integration, derivatives, and series. 
  • have studied at least one introductory programming course. The applicant should understand the notions of control structures, conditionals, variables, and functions.


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