B.学会MATLAB/R计算机编程语言。 通过应用察例学习，学会随机模拟方法处理复杂问题的能力.为理工科各专业学生计 步开创性研究打下基础. (英文300-500字) This course is about stochastic simulation methods and its applications in data science.It takes many examples of life that are easy to handle as examples,mainly introduces the basic theory and methods of statistica computingand machine indinfive-step modeling method which is composed of input,output,analysis,experiment design anc programming.This course mainly introduces the theories and methods in statistical computing about stochastic simulating,generating random numbers,Metropolis algorithms,Monte Carlo Markov Chain and its algorithm.The emphasis is to enable students to master the main ideas practice and typical application examples.At the same time,we have a general understanding of the general theory of statistical Learning Outcomes: 课程简介（英l.This course is a fundamental course in Stochastic Modeling Methods of statistical computing and machine learning.It provides th (Deseription)basic knowledge for students to research statistical computing and machine learning methods of practical complex problems and difficult mathematical problems for solving. 2.On studying the general theories and research methods of statistical machine the itanctivate the basic tcolo of suenshow engaged in the research and application fields of all different kinds of engineering and research. 3.Learn MATLAB/R computer language.At once students are required to catch corresponding algorithms and theories and to be capable of programming as well. 4.By studying the application cases in MCMC,it can cultivate the basic technology of students,who will be engaged in the research and application fields of all different kinds of engineering and research 课程目标与内容(Course objectives and contents)3．学会 MATLAB/R 计算机编程语言。 4．通过应用案例学习，学会随机模拟方法处理复杂问题的能力。为理工科各专业学生进一 步开创性研究打下基础。 *课程简介（英 文） （Description） （英文 300-500 字） This course is about stochastic simulation methods and its applications in data science. It takes many examples of life that are easy to handle as examples, mainly introduces the basic theory and methods of statistical computing and machine learning: including five-step modeling method, which is composed of input, output, analysis, experiment design and programming. This course mainly introduces the theories and methods in statistical computing about stochastic simulating, generating random numbers, Metropolis algorithms, Monte Carlo Markov Chain and its algorithm. The emphasis is to enable students to master the main ideas and basic steps and to deepen their understanding through programming practice and typical application examples. At the same time, we have a general understanding of the general theory of statistical Learning Outcomes: 1. This course is a fundamental course in Stochastic Modeling and Methods of statistical computing and machine learning. It provides the basic knowledge for students to research statistical computing and machine learning methods of practical complex problems and difficult mathematical problems for solving. 2. On studying the general theories and research methods of statistical computing and machine learning, at the same time by the developmental experiment, it can cultivate the basic technology of students, who will be engaged in the research and application fields of all different kinds of engineering and research. 3. Learn MATLAB/R computer language. At once students are required to catch corresponding algorithms and theories and to be capable of programming as well. 4. By studying the application cases in MCMC, it can cultivate the basic technology of students, who will be engaged in the research and application fields of all different kinds of engineering and research. 课程目标与内容（Course objectives and contents）