I started at ITAM in January 2023 thinking Data Science was mostly programming. The first term corrected me gently: of six courses, one was programming and three were mathematics or economics. The degree is built bottom-up, and at the bottom there are limits, vectors and demand curves.
Calculus: learning to trust the limit
Calculus I starts where high school stops: the formal definition of a limit, continuity, and why the intermediate value theorem is not obvious. The derivative stops being a recipe and becomes a question about how one thing changes when another does. What stayed with me most was the mean value theorem and Taylor’s theorem: the idea that a complicated function can be approximated locally by a polynomial is, years later, what makes almost all the machine learning I have touched possible.
Grading is departmental: three midterms and a final shared by every section. It feels demanding, but it has a virtue I came to appreciate: nobody passes on charm.
Vector Geometry: the geometry that later becomes linear algebra
Dot and cross products, lines and planes, matrices as transformations, conics as quadratic forms. At the time it looked like a course about shapes; in hindsight it is the geometric intuition that makes second-term linear algebra readable. When I project one vector onto another today to fit a regression, I am doing Vector Geometry under another name.
Algorithms and Programs
The only computing course of the term, and the most comfortable one for me: control structures, functions, arrays, binary search, sorting and recursion. The emphasis was not the language but the discipline: decompose a problem, write a function that does one thing, test it.
Economics I: the first model
Opportunity cost, the production possibility frontier, supply and demand, equilibrium, elasticities. Economics I taught me something I did not expect from a “soft” course: a model is a deliberate simplification, and the right question is not whether it is true but whether it is useful. That idea follows me every time I fit a statistical model.
Political and Social Ideas and Institutions I
The general-studies course that defines ITAM. We read Sophocles, Plato and Aristotle, then Cicero, Seneca and Augustine, and finished with Aquinas and Dante. The class is a dialogue: you arrive having read the text and you discuss it. At first I did not understand what a class on Plato’s Republic was doing in a data degree. Now I think it is the course that teaches you to ask “what is just?” before asking “what is optimal?”, and that question eventually reaches anyone who decides with data.
What I take with me
That the degree is a pyramid and the first term is the foundation. And that ITAM does not separate the technical from the human: it hands you both in the same week and expects you to learn to carry them together.