Featured Key Projects
This section showcases some of my recent key projects. You could click on each card to know the detailed process of each project. For all projects, please navigate to the Projects page.
Coursework
This section highlights my relevant coursework in Machine Learning, Statistics, Mathematics and Data Sciences. You can click the links to see my course deliverables/assignments for each course.
Duke University
- Principles of Machine Learning taught by Dr. Kyle Bradbury
- Introduction to Deep Learning taught by Prof. Vahid Tarokh
- Modelling and Representation of Data taught by Dr. Olanrewaju M. Akande
- Data Analysis at Scale in Cloud taught by Noah Gift
- Introduction to Data Scraping and Text Analysis taught by Prof. Christopher Andrew Bail
- Computational Topology (TDA) taught by Prof. John Harer
- Introduction to High Dimensional Data Analysis taught by Dr. Paul L Bendich
- Bayesian and Modern Statistics taught by Dr. Olanrewaju M. Akand
- Data Science Ethics
- Data Logic, Visualization and Storytelling
- Advanced Game Theory
Online Learning
- Udemy: Maxima and Minima concepts : Applications of Derivatives
- Udemy: Particle Swarm Optimization in MATLAB
- Coursera Specialization: Mathematics for Machine Learning- Linear Algebra , Multivariate Calculus and PCA
- Coursera: Advanced Linear Models for Data Science 1: Least Squares
- Coursera: Advanced Linear Models for Data Science 2: Statistical Linear Models
- Coursera: Combinatorics and Probability
- Coursera: Data Science Math Skills
- Coursera: Introduction to Graph Theory
- edX: AP® Calculus: Challenging Concepts from Calculus AB & Calculus BC (audited the course)
Ongoing Pursuits
Coursework
- Duke: Causal Inference
- Duke: Social Network Analysis
- Duke: Numerical Optimization
- Nvidia: CUDA Education and Training
Projects
- Amazon Last Mile Routing Research Challenge
- Course project: Study of research co-authorship networks
Contact Me
Address
Duke University, Durham, NC, USAPhone Number
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