The third term was the first in which the courses seemed to talk to each other without anyone planning it.
Data Structures
Linked lists, stacks, queues, iterators, trees, graphs and their adjacency-matrix representation, and the tool that changes how you see every program you write afterwards: Big-O notation. Before this course a program “worked or did not work”. After it, it works in O(n log n) or in O(n²), and that difference decides whether something runs in a second or in a week once the data grows. Today, when I design a table or a data job, that is the first question I ask.
Discrete Mathematics
Counting, inclusion-exclusion, recurrence relations, graph theory, some combinatorics and logic. It is the mathematics of things that are counted rather than measured, and it underlies both discrete probability and algorithms.
Calculus III
Functions of several variables, partial derivatives, the gradient, the Hessian, Lagrange multipliers, the implicit function theorem, multiple integrals, the Jacobian. The gradient is the idea I use most: the gradient descent that trains almost every modern model is literally “walk against the derivative”. And Lagrange is the formal version of what Economics II did intuitively when maximizing utility under a budget.
Economics III
Macroeconomics: national accounts, the IS-LM model, comparative statics, the open economy, fiscal and monetary policy. After two terms of individual agents, seeing the economy as an aggregate system with feedback made me think of data pipelines: flows, stocks, and what happens when one component changes.
Ideas and Institutions III
The contemporary part: Comte, Mill and Marx under the heading “capitalism and social revolution”; then Nietzsche, Freud and Bergson in the age of imperialism; and to close the twentieth century, Wittgenstein and Heidegger. It is the term of critiques: of reason, of progress, of language. Reading Marx after three terms of neoclassical economics is uncomfortable and necessary; you do not have to agree to understand what is being criticized.
Problems of Contemporary Civilization II
Population and habitat, humans as creators and carriers of culture, education and development. Questions the technical degree does not ask on its own appeared here for the first time: who benefits from a technology, what is lost when something is optimized.
What I take with me
That the cost of an algorithm and the cost of a public decision are more alike than I thought: both are measured in what you give up, not in what you gain.