Semester.ly

Johns Hopkins University | EN.550.433

Monte Carlo Methods

4.0

credits

Average Course Rating

(4.05)

The objective of the course is to survey essential simulation techniques for popular stochastic models. The stochastic models may include classical time-series models, Markov chains and diffusion models. The basic simulation techniques covered will be useful in sample-generation of random variables, vectors and stochastic processes, and as advanced techniques, importance sampling, particle filtering and Bayesian computation may be discussed.

Fall 2012

(4.09)

Fall 2013

(3.69)

Fall 2014

(4.38)

Fall 2012

Professor: James Spal

(4.09)

16 Students found the material interesting and said the professor was engaging and passionate about the topic. The course provided useful and practical skills. The homework was difficult, but helped students understand the material. Suggestions for improvement included having sample exams or more homework problems to prepare for exams. Students should have a strong background in probability and experience with programming.

Fall 2013

Professor: James Spal

(3.69)

Students found this course to be very enjoyable because of its diverse content and the very practical coding techniques taught over the semester. Students felt that they learned a very solid understanding of MATLAB and R programming, and that they wil be able to apply what they learned to everyday issues. Students felt that the homework was difficult and work-heavy and that the assignments did not really prepare them for the quizzes. Students also thought that the professor would direct them back to the reading or told them to try multiple things before he would answer questions, if he did at all. Students suggested spending more time with concrete examples for each concept, spending more time on a lessened syllabus. They wanted more practical applications of what they were learning, as well as more guidance in figuring out problems. Prospective students should have some background knowledge in linear algebra, calculus, and programming, as well as knowing upper level probability.

Fall 2014

Professor: James Spal

(4.38)

Students found that their favorite aspect of this class was the usefulness and practicality of the material covered. However, they disliked the large amount of homework assignments in the course. Some thought the course could be improved by looking into the subject matter in greater depth. Students also thought the addition of an assigned project might be helpful. People thinking about taking this class should know that previous experience with both statistics and probability would be valuable for this course, students said.