(P.S. Both sections of BIOS 524 are equivalent, with only minimal differences due to the variation in platform/mode of teaching.)
Topics:
R: Introduction to R
R: R objects and functions
R: Good coding habits in R
R: Faster R techniques
R: Parallel computing
R: Writing R package
R: Introduction to RCPP
SAS: Introduction to SAS
SAS: Import and export data
SAS: Writing functions
SAS: Fitting statistical models.
Topics:
Revisit to R (Good coding habits + Faster R techniques)
Coding in C++ and RCPP (using R Studio interface)
Writing R and RCPP packages
Coding in MATLAB
CPU and GPU parallel computing
EM and MM algorithms
Convex optimization
Optimization tools in MATLAB
Black-box/global optimization tools
Application case studies of optimization related problems in statistics and related fields
Bootstrap
Topics:
Introduction to Python
PyChram IDE
Python objects
Modules: NumPy, Matplotlib, Pandas
Topics:
Estimation and hypothesis testing when the form of the underlying distribution is unknown
One, two and k-sample problems
Tests of randomness
Kolmogorov-Smirnov tests
Analysis of contingency tables and coefficients of association.
Basis functions: polynomial, spline, Bernstein polynomial and other related techniques
Tree regression
Kaplan Meier estimator