This page contains syllabi, problem sets, past exams, and other resources for the courses that I am currently teaching and have taught in the past.
From the calendar: A hands-on introduction to astronomical observing using the UTSC telescopes. Lectures cover topics of astronomical instrumentation and data reduction. Observations of Solar System planets, moons, planetary nebula, globular clusters and galaxies will be made. Students will present their results in the style of a scientific paper and a talk.
From the calendar: A hands-on introduction to astronomical observing using the UTSC telescopes. Lectures cover topics of astronomical instrumentation and data reduction. Observations of Solar System planets, moons, planetary nebula, globular clusters and galaxies will be made. Students will present their results in the style of a scientific paper and a talk.
Note that the course is currently scheduled as in person. Depending on the current state of the pandemic, the course might be switched to online synchronous for some or all of the lectures.
Please see Quercus for updates regarding this course.
From the calendar: Scientific computing is a rapidly growing field because computers can solve previously intractable problems and simulate natural processes governed by equations that do not have analytic solutions. During the first part of this course, students will learn numerical algorithms for various standard tasks such as root finding, integration, data fitting, interpolation and visualization. In the second part, students will learn how to model real-world systems from various branches of science. At the end of the course, students will be expected to write small programs by themselves. Assignments will regularly include programming exercises.
Note that the course is currently scheduled as in person. Depending on the current state of the pandemic, the course might be switched to online synchronous for some or all of the lectures.
Please see Quercus for updates regarding this course.
From the calendar: Scientific computing is a rapidly growing field because computers can solve previously intractable problems and simulate natural processes governed by equations that do not have analytic solutions. During the first part of this course, students will learn numerical algorithms for various standard tasks such as root finding, integration, data fitting, interpolation and visualization. In the second part, students will learn how to model real-world systems from various branches of science. At the end of the course, students will be expected to write small programs by themselves. Assignments will regularly include programming exercises.
Note that the course is currently scheduled as in person. Depending on the current state of the pandemic, the course might be switched to online synchronous for some or all of the lectures.
Please see Quercus for updates regarding this course.
Since ancient times, humans have observed the night sky. One of the most striking feature easily observable with the naked eye are planets, the wandering stars. For centuries astronomers have recorded and predicted their motion. This course introduces graduate students to three topics in the wide field of Planetary Dynamics. Note that students can opt to take only one or two out of the three mini-courses being offered. But note that each mini-course builds on the knowledge developed during the previous mini-course(s).
You can download a tentative syllabus. If you would like to take this course, please get in touch via e-mail.
From the calendar: Scientific computing is a rapidly growing field because computers can solve previously intractable problems and simulate natural processes governed by equations that do not have analytic solutions. During the first part of this course, students will learn numerical algorithms for various standard tasks such as root finding, integration, data fitting, interpolation and visualization. In the second part, students will learn how to model real-world systems from various branches of science. At the end of the course, students will be expected to write small programs by themselves. Assignments will regularly include programming exercises.
Please see Quercus for updates regarding this course.
From the calendar: Scientific computing is a rapidly growing field because computers can solve previously intractable problems and simulate natural processes governed by equations that do not have analytic solutions. During the first part of this course, students will learn numerical algorithms for various standard tasks such as root finding, integration, data fitting, interpolation and visualization. In the second part, students will learn how to model real-world systems from various branches of science. At the end of the course, students will be expected to write small programs by themselves. Assignments will regularly include programming exercises.