Relevant Course Work

Non-traditional Course Work/Professional Development:

SAMSI Optimization Program - Summer School:
- EM/MM Algorithms and their Modern Applications
- Optimization for Statistics and Machine Learning
- Lagrangian Duality and KKT Conditions
IEEE BIBM Conference Workshops:
- Nonnegative Matrix Factorization and Tensor Decomposition Techniques for High-Throughput Biological Data Analysis
Machine Learning
- Learning Platform: Coursera.org
- Instructor: Dr. Andrew Ng
- Topics covered:
  - supervised machine learning techniques such as neural nets and the support vector machine
  - unsupervised machine learning techniques such as Principal Component Analysis and K-means clustering
R software
- Learning Platform: DataCamp.com
- Instructor(s): various
- Topics covered:
  - Importing and cleaning data from various files/databases such as Excel files, database SQL/SPSS files
  - Data visualization using ggplot
  - Data manipulation using dplyr
  - Statistical data analysis methods: t-tests, ANOVA

Traditional Course Work via North Carolina State University: