美國康奈爾大學(xué)金融工程碩士申請解析
Master of Engineering- Financial Engineering 康奈爾大學(xué)工程碩士，金融工程方向，設(shè)于學(xué)院School of Operations Research and Information Engineering(ORIE)之下，學(xué)制3學(xué)期(1.5年)，秋季學(xué)期開學(xué)，至少修滿30學(xué)分。第一、三學(xué)期，學(xué)生會(huì)在紐約州的Ithaca校區(qū)上課，第二學(xué)期會(huì)在紐約市的曼哈頓校區(qū)上課。
申請要點(diǎn)
◇ 僅接受GRE分?jǐn)?shù),不接收GMAT分?jǐn)?shù)，最近幾年被錄取學(xué)生V部分的中位數(shù)分?jǐn)?shù)為165分，Q部分為166分，分析寫作為3.5分
◇ TOEFL分?jǐn)?shù)100分以上(寫作不低于20分，聽力不低于15分，閱讀不低于20分，口語不低于22分)， IELTS分?jǐn)?shù)7.0分以上
◇ 無工作經(jīng)驗(yàn)要求
◇ 申請截止日期： 12月1日
◇ 學(xué)費(fèi)： $26,306.00/學(xué)期
課程設(shè)置
優(yōu)化建模課程(Optimization Modeling Courses):
Revenue Optimization and Marketplace Design
Nonlinear Optimization
Discrete Models
Intro to Game Theory
Spreadsheet-Based Modeling and Data Analysis
Inventory Management
Optimization I
Optimization II
Topics in Linear Optimization
Optimization Modeling in Finance
隨機(jī)建模課程(Stochastic Modeling Courses):
Revenue Optimization and Marketplace Design
ntro to Financial Engineering
OR Tools for Financial Engineering
Inventory Management
Service System Modeling and Design
Prob and Stat II
Simulation Modeling and Analysis
Monte Carlo Simulation
Monte Carlo Methods in FE
Stochastic Processes
Intro to Engineering Stochastic Processes II
Financial Engineering with Stochastic Calculus I
Financial Engineering with Stochastic Calculus II
Credit Risk: Modeling, Valuation, and Mgmt
Quantitative Methods of Financial Risk Mgmt
數(shù)據(jù)科學(xué)與統(tǒng)計(jì)建模課程(Data Science and Statistical Modeling Courses):
OR Tools for Financial Engineering
Statistical Data Mining I
Learning with Big Messy Data
Information Theory, Probabilistic Modeling, & Deep Learning with Scientific & Financial Applications
Applied Time Series Analysis
Statistics for Financial Engineering
Machine Learning for Intelligent Systems
Machine Learning for Data Science
Linear Models with Matrices
Theory of Statistics
Data Mining and Machine Learning
Bayesian Data Analysis: Principles and Practice
金融選修課：
Comprehensive Financial Statement Analysis
Investments and Portfolio Analysis
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