### Independent Learning Projects

**Dec 2018**

**Learning Project**,

*Machine Learning - Cousera - Stanford*

This course taught me about about a diverse set concepts and algorithms used for applying machine learning including: gadient descent, k-means clustering, techniques for neogtiating bias and variance, and nueral networks.

**May 2019 - Present**

**Learning Project**,

*Introduction to Databases - Stanford Lagunita*

This course covered the XPath and SQL query languages, efficiently designing database
schemes by analyzing dependences and using normal forms, as well as semi-structured
data in the form of JSON and XML.

**Dec 2018**

**Learning Project**,

*Introduction to Probablity - Open Courseware - MIT*

An extensive course in Probability Theory and Statistical Inference. I canâ€™t
wait apply Bayesian inference, Monty Carlo Simulations and probability distributions to
future data science projects. In particular, I am excited to use what I learned in the course
in a signal processing/computer vision context.