E.g., Thursday, December 18, 2014
E.g., Thursday, December 18, 2014
E.g., Thursday, December 18, 2014
Self Paced

This course follows on from FE & RM Part I. We will consider portfolio optimization, risk management and some advanced examples of derivatives pricing that draw from structured credit, real options and energy derivatives. We will also cast a critical eye on how financial models are used in practice.

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This course provides an introduction to various classes of derivative securities and we will learn how to price them using "risk-neutral pricing". In the follow-up to this course (FE & RM Part II) we will consider portfolio optimization, risk management and more advanced examples of derivatives pricing including, for example, real options and energy derivatives.

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A matemática é a ciência do raciocínio lógico e abstrato, estuda quantidades, medidas, espaços, estruturas e variações. Um trabalho matemático consiste em procurar por padrões, formular conjecturas e, por meio de deduções rigorosas a partir de axiomas e definições, estabelecer novos resultados.

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Learn what it takes to become a data scientist.

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This FREE MOOC (Massive Open Online Course) investigates the use of clouds running data analytics collaboratively for processing Big Data to solve problems in Big Data Applications and Analytics. Case studies such as Netflix recommender systems, Genomic data, and more will be discussed.

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This course will introduce you to the fundamentals of probability theory and random processes. The theory of probability was originally developed in the 17th century by two great French mathematicians, Blaise Pascal and Pierre de Fermat, to understand gambling.

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A real Caltech course, not a watered-down version. This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications.

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Self Paced

This Research Methods Lab course is part two of the Research Methods series. You should not attempt this course without having first completed the "Research Methods" course. This Lab extends beyond the basics of research methodology and the logic of experimental design, concepts you learned in "Research Methods".

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This course will introduce you to business statistics, or the application of statistics in the workplace.Statistics is a course in the methods for gathering, analyzing, and interpreting data.

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In this course, you will look at the properties behind the basic concepts of probability and statistics and focus on applications of statistical knowledge.

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Meteorology is fundamental for sailing safety and is the very essence of strategy for winning any regatta. It is also the science most directly linked to ocean sailing.

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Based on Next Generation Science Standards, this course provides an introduction to the role of science in society, feedback and regulation mechanisms, and using a systems approach to solve scientific problems. Participants will explore the nature of scientific inquiry and learn how to analyze scientific data.

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Investigate, Visualize, and Summarize Data Using R.

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Can we program machines to learn like humans? This Reinforcement Learning course will teach you the algorithms for designing self-learning agents like us!

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Ever wonder how Netflix can predict what movies you'll like? Or how Amazon knows what you want to buy before you do? The answer can be found in Unsupervised Learning!

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En este curso de Probabilidad y Estadística estudiamos dos áreas fundamentales del conocimiento: La Probabilidad como una rama de las matemáticas que mide cuantitativamente la posibilidad de que un experimento produzca un determinado resultado, y la Estadística como ciencia formal que estudia la recolección, análisis e interpretación de datos de una muestra.

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The course aims to present an overview of the main management methods and techniques used in the field of industrial contexts to achieve the objectives of Quality.

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This course covers Supervised Learning, a machine learning task that makes it possible for your phone to recognize your voice, your email to filter spam, and for computers to learn a bunch of other cool stuff.

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Data Manipulation and Retrieval. In this course, we will explore how to wrangle data from diverse sources and shape it to enable data-driven applications. Some data scientists spend the bulk of their time doing this!

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Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.

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