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Note: This course is offered by Stanford as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development. This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric...more
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Note: This course is being offered this summer by Stanford as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development. 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....more
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Stanford University offers XCS193H: High Performance Websites as a self-paced online course for professionals. Course Description: People love fast web sites, but up until now developers have been focusing on the wrong area. Backend (web server, database, etc.) performance is important for reducing hardware costs and improving efficiency, but for most pages 80% of the load time is spent on the frontend (HTML, CSS, JavaScript, images,...more
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Note: This course is being offered by Stanford this summer as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development. 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++...more
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Introduction to Chemical Engineering (E20) is an introductory course offered by the Stanford University Engineering Department. It provides a basic overview of the chemical engineering field today and delves into the applications of chemical engineering.
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This is a math course aimed at students with life science majors covering elementary probability, probability distributions, random variables, and limit theorems.
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This is an introductory chemistry course, emphasizing basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis. This course also introduces the chemistry of biological, inorganic, and organic molecules.
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This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics...more
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This is an introductory course in Greek history tracing the development of Greek civilization as manifested in political, intellectual, and creative achievements from the Bronze Age to the end of the classical period. Students read original sources in translation as well as the works of modern scholars.
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Programming Methodology is the largest of the introductory programming courses and is one of the largest courses at Stanford. Topics focus on the introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Programming Methodology teaches the widely-used Java programming language along with good software...more
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Earth & Space Science 15: Introduction to Oceanography is a class that provides a general introduction to geological, physical, chemical, and biological processes and history of Earth's global oceanic system. Edwin Schauble is an Associate Professor from UCLAs Department of Geochemistry and Astrobiology. His current area of study and collaboration include species-dependent isotopic signatures in dissolved iron, spectroscopic signatures...more
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This is a basic course on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices.
