data-oriented programming

The first lecture of Stanford's CS107 Programming Paradigms, taught by Jerry Cain, giving an overview of the course. The course goes from C and assembly through C++, concurrency, Scheme and Python.

First lecture of Stanford's CS106A Programming Methodology by Mehran Sahami, giving a course overview and starting on programming. The course teaches software engineering principles using Java.

The first lecture of MIT's 1986 6.001 Structure and Interpretation of Computer Programs, given by Harold Abelson, introducing Lisp and the idea of computer science as the study of process.

An eight-minute excerpt of a 1983 video featuring Seymour Papert, creator of Logo, on children learning programming and abstract ideas through embodied play. It shows kids acting out the Logo turtle.

Lecture 1B of MIT's 6.001 Structure and Interpretation of Computer Programs (1986) with Gerald Sussman, covering procedures, processes and the substitution model. It includes the line about the power of naming things.

An excerpt from Hal Abelson's opening SICP lecture introducing computer science and contrasting declarative and imperative knowledge. He argues that computer science is not really a science and is more like magic or engineering of ideas.

Harvard physicist Eric Mazur explains how he realized his students were memorizing rather than understanding, and how he changed his teaching. He presents peer instruction and data showing improved student performance.

Elizabeth Warren's 2007 Berkeley lecture, when she was a Harvard law professor, on why middle-class families are under growing financial strain. She draws on bankruptcy research to examine rising costs of housing, health care and education.

Ian Piumarta's 2007 Stanford EE380 lecture on building a dynamic programming environment from the ground up, from the Viewpoints Research Institute's work. It covers the design of a language and system with a recursive design, parsing through code generation, and the COLA architecture.

The introductory lecture of Stephen Boyd's Stanford Convex Optimization I course (EE 364A). It outlines convex sets, functions and problems, and the course's coverage of least-squares, linear and semidefinite programming, duality and interior-point methods.