stanford-engineering

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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

http://see.stanford.edu/see/courseinfo.aspx?coll=17005383-19c6-49ed-9497-2ba8bfcfe5f6
Continuation of Convex Optimization I. http://see.stanford.edu/see/courseinfo.aspx?coll=523bbab2-dcc1-4b5a-b78f-4c9dc8c7cf7a

School of Engineering - Stanford Engineering Everywhere

http://see.stanford.edu/see/courseinfo.aspx?coll=84d174c2-d74f-493d-92ae-c3f45c0ee091 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

http://see.stanford.edu/see/courseinfo.aspx?coll=2db7ced4-39d1-4fdb-90e8-364129597c87

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#. http://see.stanford.edu/see/courseinfo.aspx?coll=2d712634-2bf1-4b55-9a3a-ca9d470755ee
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

http://see.stanford.edu/see/courseinfo.aspx?coll=11f4f422-5670-4b4c-889c-008262e09e4e

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. http://see.stanford.edu/see/courseinfo.aspx?coll=824a47e1-135f-4508-a5aa-866adcae1111
http://see.stanford.edu/see/courseinfo.aspx?coll=348ca38a-3a6d-4052-937d-cb017338d7b1 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

http://see.stanford.edu/see/courseinfo.aspx?coll=63480b48-8819-4efd-8412-263f1a472f5a

School of Engineering - Stanford Engineering Everywhere

http://see.stanford.edu/see/courseinfo.aspx?coll=86cc8662-f6e4-43c3-a1be-b30d1d179743 The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems.