Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. School of Engineering - Stanford Engineering Everywhere
Continuation of Convex Optimization I. School of Engineering - Stanford Engineering Everywhere
The goals for the course are to gain a facility with using the Fourier transform, both specific techniques and general principles, and learning to recognize when, why, and how it is used. Together with a great variety, the subject also has a great coherence, and the hope is students come to appreciate both. Topics include: The Fourier transform as a tool for solving physical problems. School of Engineering - Stanford Engineering Everywhere
School of Engineering - Stanford Engineering Everywhere Concentrates on recognizing and solving convex optimization problems that arise in engineering.
School of Engineering - Stanford Engineering Everywhere Advanced memory management features of C and C++; the differences between imperative and object-oriented paradigms. The functional paradigm (using LISP) and concurrent programming (using C and C++). Brief survey of other modern languages such as Python, Objective C, and C#.
This course is the natural successor to Programming Methodology and covers such advanced programming topics as recursion, algorithmic analysis, and data abstraction using the C++ programming language, which is similar to both C and Java. If you've taken the Computer Science AP exam and done well (scored 4 or 5) or earned a good grade in a college course, Programming Abstractions may be an appropriate course for you to start with, but often Programming Abstractions (Accelerated) is a better choice. School of Engineering - Stanford Engineering Everywhere
This course is the largest of the introductory programming courses and is one of the largest courses at Stanford.
This course provides a broad introduction to machine learning and statistical pattern recognition. School of Engineering - Stanford Engineering Everywhere
This course is designed to introduce students to the fundamental concepts and ideas in natural language processing (NLP), and to get them up to speed with current research in the area. School of Engineering - Stanford Engineering Everywhere
School of Engineering - Stanford Engineering Everywhere The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems.