Useful courses I took in McGill
- COMP 540 Matrix Computation
- - The course covers topics on linear systems (LU factorization, Cholesky factorization, QR factorization), least squares problem, singular value decomposition, eigenvalue problems, numerical stability of algorithms.
- COMP 652 Machine Learning
- - The course covers topics on machine learning algorithms and methods including linear regression, polynomial regression, logistic regression, neural networks, decision trees, instance-based learning, boosting, Support vector machines and kernels. Overfitting problems in learning and regularization, cross validation.
- COMP 512 Distributed Systems
- - Communication basics( Network types, communication layers, TCP/UDP, IP protocal);
- - Remote Method Invocation;
- - Group communications( Multicast communication);
- - Distributed transcations( Concurrency control, atomic commit protocols, local recovery, replication)
- COMP 610 Information Structure
- - Data structures( list, stacks, queues, trees, hashtables, binary search trees, red-black trees, heaps);
- - Sorting and selection( quicksort, mergesort, bucket sort)
- - Data structure in compression(Huffman trees, digital trees and tries);
- - Paradigms for algorithms( greedy methods, dynamic programming, string matching).
Teaching assistant on courses
- COMP 208 Computers in Engineering
- - The course gives an introduction to computer systems. Topics covers introduction to FORTRAN and C programming,
sort and search algorithms, numerical algorithms such as root finding, numerical integration and differential equations.
- - My duty included grading assignments and giving tutorials on programming exercises.
- COMP 251 Algorithms and Data Structures
- - Course topics covers graphs and basic graph algorithms, greedy algorithms, divide and qonquer, dynamic programming.
- - My duty included grading assignments and giving extra tutorials.