Teaching Assistant, McGill University
This is a new course offered by McGill that introduces undergraduate students to statistical computing methods in R. I wrote and presented weekly tutorials delivered remotely. Furthermore, I graded midterm exams and held twice-weekly office hours.
Topics Covered: Basic data management. Data visualization. Exploratory data analysis and descriptive statictics. Writing functions. Simulation and parallel computing. Communication data and documenting code for reproducible research.
I wrote and presented lectures on the topics of convex analysis, convex optimization, and Lagrangian duality. Furthermore, I was repsonible for grading homework assignments.
Topics Covered: Optimization in machine learning. Support vector machines. Regularization. Generalization theory. Adversarial robustness. Losses for classification.
I wrote and presented lectures twice a week on various topics in the theory of linear algebra. Furthermore, I held office hours and was reponsible for grading midterms and final exams.
Topics Covered: Review of matrix algebra, determinants and systems of linear equations. Vector spaces, linear operators and their matrix representations, orthogonality. Eigenvalues and eigenvectors, diagonalization of Hermitian matrices. Applications.