Introduces the fundamentals of linear algebra in the context of computer science applications. Includes vector spaces, matrices, linear systems, and eigenvalues.

Computations that involve matrix algorithms are happening everywhere in the world at every moment in time, whether these be embedded in the training of neural networks in data science, in computer ...

Instructor Fall 2016: Sriram SankaranarayananPrerequisitesCalculus I,II + Algorithms + Linear Algebra.Topics CoveredRoughly, we will cover the following topics (some of them may be skipped depending ...

BS in Computer Science Concentration: ApplicationsLab Science Requirements: 7 Credits Minimum Students must complete two science courses in two different disciplines (BL, CH, KIP, FW, GE, PH, SS) from ...

Familiarity with linear algebra is expected. In addition, students should have taken a proof-based course such as CS 212 or Math 300. Tensors, or multiindexed arrays, generalize matrices (two ...

Harvard offers free courses in multiple subject areas including Arts and Design, Theology, Business, Computer Science, Data ...