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\n\t\t\t\tWe are now at the era of big data. Companies are able to collect tremendous amount of data, very often more than necessary, with ease. “Information is Power” is no longer valid if companies are not able to make correct decision timely out of the data. The use of business analytics for modeling and decisions represents the future of best practices for tomorrow’s success companies. \n\t\t\t\t \n\t\t\t\tThis course prepares students with fundamental theory and basic instruments to capture business insights from data and thus make good managerial decisions. Quantitative models and tools such as Decision Analysis, Simulation Modeling and Mathematical Optimization are covered to demonstrate the use of scientific methods in business decision making. Practical examples and cases with rich data are used to stimulate students’ interest and understanding in Business Analytics. \n\t\t\t\t | \n\t\t
\n\t\t\t\tWeek | \n\t\t\t\n\t\t\t\tTitle | \n\t\t\t\n\t\t\t\tTopics Covered | \n\t\t
\n\t\t\t\t1 | \n\t\t\t\n\t\t\t\tIntroduction to Business Analytics | \n\t\t\t\n\t\t\t\t· Course overview \n\t\t\t\t· Introduction to B.A. \n\t\t\t\t· Basic probability theories | \n\t\t
\n\t\t\t\t2 | \n\t\t\t\n\t\t\t\tProbability Theory | \n\t\t\t\n\t\t\t\t· Conditional probability \n\t\t\t\t· Bayes’ theorem \n\t\t\t\t | \n\t\t
\n\t\t\t\t3 | \n\t\t\t\n\t\t\t\tDecision Tree | \n\t\t\t\n\t\t\t\t· Introduction to Decision Tree \n\t\t\t\t· Decision Tree analysis with probability | \n\t\t
\n\t\t\t\t4 | \n\t\t\t\n\t\t\t\tDiscrete Probability | \n\t\t\t\n\t\t\t\t· Discrete probability distributions \n\t\t\t\t· Summary measures of probability distributions \n\t\t\t\t· Linear functions of a random variable | \n\t\t
\n\t\t\t\t5 | \n\t\t\t\n\t\t\t\tContinuous Probability Distributions | \n\t\t\t\n\t\t\t\t· Introduction to continuous probability distributions \n\t\t\t\t· Exponential Distribution \n\t\t\t\t· Normal Distribution | \n\t\t
\n\t\t\t\t6 | \n\t\t\t\n\t\t\t\tSimulation Modeling | \n\t\t\t\n\t\t\t\t· Simulation modeling | \n\t\t
\n\t\t\t\t7 | \n\t\t\t\n\t\t\t\tIntroduction to Linear Optimization | \n\t\t\t\n\t\t\t\t· What is linear optimization? \n\t\t\t\t· Modeling linear optimization problems | \n\t\t
\n\t\t\t\t8 | \n\t\t\t\n\t\t\t\tThe Geometry of Linear Programming | \n\t\t\t\n\t\t\t\t· Graphical solution of LP \n\t\t\t\t· Binding and non-binding constraints | \n\t\t
\n\t\t\t\t9 | \n\t\t\t\n\t\t\t\tSensitivity Analysis | \n\t\t\t\n\t\t\t\t· Introduction to sensitivity analysis \n\t\t\t\t· Shadow price and its business interpretation | \n\t\t
\n\t\t\t\t10 | \n\t\t\t\n\t\t\t\tDiscrete Optimization | \n\t\t\t\n\t\t\t\t· Integer programming \n\t\t\t\t· Binary optimization \n\t\t\t\t· Mixed integer programming | \n\t\t
\n\t\t\t\t11 | \n\t\t\t\n\t\t\t\tApplication of Optimization | \n\t\t\t\n\t\t\t\tCase study | \n\t\t
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\tWeek | \n\t\t\t\n\t\t\t\tTitle | \n\t\t\t\n\t\t\t\tTopics Covered | \n\t\t
\n\t\t\t\t1 | \n\t\t\t\n\t\t\t\tIntroduction | \n\t\t\t\n\t\t\t\t· Course overview \n\t\t\t\t· Introduction to B.A. \n\t\t\t\t· Basic probability theories | \n\t\t
\n\t\t\t\t2 | \n\t\t\t\n\t\t\t\tIntroduction to Probability Theory | \n\t\t\t\n\t\t\t\t· Conditional probability \n\t\t\t\t· Bayes’ theorem | \n\t\t
\n\t\t\t\t3 | \n\t\t\t\n\t\t\t\tDiscrete Probability | \n\t\t\t\n\t\t\t\t· Discrete probability distributions \n\t\t\t\t· Summary measures of probability distributions \n\t\t\t\t· Linear functions of a random variable | \n\t\t
\n\t\t\t\t4 | \n\t\t\t\n\t\t\t\tContinuous Probability Distributions | \n\t\t\t\n\t\t\t\t· Introduction to continuous probability distributions \n\t\t\t\t· Exponential Distribution \n\t\t\t\t· Normal Distribution | \n\t\t
\n\t\t\t\t5 | \n\t\t\t\n\t\t\t\tIntroduction to Simulation Modeling | \n\t\t\t\n\t\t\t\t· Simulation modeling | \n\t\t
\n\t\t\t\t6 | \n\t\t\t\n\t\t\t\tCancel | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t7 | \n\t\t\t\n\t\t\t\tIntroduction to Linear Optimization | \n\t\t\t\n\t\t\t\t \n\t\t\t\t· What is linear optimization? \n\t\t\t\t· Modeling linear optimization problems | \n\t\t
\n\t\t\t\t8 | \n\t\t\t\n\t\t\t\tDecision Tree | \n\t\t\t\n\t\t\t\t· Introduction to Decision Tree \n\t\t\t\t· Decision Tree analysis with probability | \n\t\t
\n\t\t\t\t9 | \n\t\t\t\n\t\t\t\tDiscrete Optimization | \n\t\t\t\n\t\t\t\t· Integer programming \n\t\t\t\t· Binary optimization \n\t\t\t\t· Mixed integer programming | \n\t\t
\n\t\t\t\t10 | \n\t\t\t\n\t\t\t\tThe Geometry of Linear Programming | \n\t\t\t\n\t\t\t\t· Graphical solution of LP \n\t\t\t\t· Binding and non-binding constraints | \n\t\t
\n\t\t\t\t11 | \n\t\t\t\n\t\t\t\tSensitivity Analysis & Shadow Price | \n\t\t\t\n\t\t\t\t· Introduction to sensitivity analysis \n\t\t\t\t· Shadow price and its business interpretation | \n\t\t
\n\t\t\t\t12 | \n\t\t\t\n\t\t\t\tProject presentation, I | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t13 | \n\t\t\t\n\t\t\t\tProject presentation, II | \n\t\t\t\n\t\t\t\t | \n\t\t