engineering systems


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  1. A good entrepreneurial company requires a variety of people with diverse skills, says Hennessy.  Though there is a natural tendency to focus on the technology side of the company, non-engineering people are just as critical as the engineering people.  In addition, the success of a venture is not based solely on the skills of the technical employees, but on the ability of the team to work together.

  2. A Wrap Up of Multi-dimensional Arrays, The ArrayList Way, Pros and Cons : ArrayList vs. Array, Debugging, Approaches to Debugging, The Debugger in Eclipse

  3. Guest Lecturer: Keith Schwarz, About the C++ Language, Quick History of C++, C++ Philosophy, C++ Without genlib.h, A Working genlib.h Replacement, Other CS106 Headers, strutils.h, simpio.h, random.h, graphics.h/extrgraph.h, What about ADTs?, Standard Template Library, STL Algorithms, Language Features, Operator Overloading, What Next?

  4. About the Introduction to Computer Science Series at Stanford, The Philosophy, Why take CS106B?, Logistics of the Course, Introducing C++

  5. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.

  6. Abstract Data Types, Wall of Abstraction, Why ADTs?, Live Coding Example: Creating the Vector Class, Private Data Members, Growing Dynamically: Making Space at Runtime, Insert and Remove Functions, Templatizing the Class Created, Including the "template.cpp" - Why?

  7. Addendum: Hit-And-Run CG Algorithm, Maximum Volume Ellipsoid Method, Chebyshev Center Method, Analytic Center Cutting-Plane Method, Extensions (Of Cutting-Plane Methods), Dropping Constraints, Epigraph Cutting-Plane Method, PWL Lower Bound On Convex Function, Lower Bound, Analytic Center Cutting-Plane Method, ACCPM Algorithm, Constructing Cutting-Planes, Computing The Analytic Center, Infeasible Start Newton Method Algorithm, Properties (O...more

  8. Advice for Applying Machine Learning, Debugging Reinforcement Learning (RL) Algorithm, Linear Quadratic Regularization (LQR), Differential Dynamic Programming (DDP), Kalman Filter & Linear Quadratic Gaussian (LQG), Predict/update Steps of Kalman Filter, Linear Quadratic Gaussian (LQG)

  9. This course offers a holistic view of the aircraft as a system, covering: basic systems engineering; cost and weight estimation; basic aircraft performance; safety and reliability; lifecycle topics; aircraft subsystems; risk analysis and management; and system realization. Small student teams retrospectively analyze an existing aircraft covering: key design drivers and decisions; aircraft attributes and subsystems; and operational experien...more