A Little Information About Me

Computer Science Graduate seeking opportunities in the fields of software and web development, specializing in C# and fullstack ASP.Net development. Successful in taking new and original projects from inception, to launch, and to long term continuation. Team oriented individual with over 7 years of experience as both a leader and collaborator. Forever curious and enthusiastically eager to learn new technologies and concepts.

Lanuages and Technologies I Use

My day to day development is with C#, fullstack Asp.Net, JavaScript, SQL Server and Postgresql. I also regularly use Python in conjunction with SciKit Learn and Pandas for machine learning, I am particularly interested in using machine learning for price prediction and regression analysis.

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My Portfolio

Here are a few of the many projects I've worked on that I am particularly proud of.

Person writing tasks in notebook Photo by Glenn Carstens-Peters on Unsplash

Task Tracker

A task tracking web application where users can log in and create a reminder for a task they want to perform. They can classify their tasks by catergory, add a start and end time. If a user so desires, they can update any task they want, and also delete a task when it is completed. Built with Boostrap 5, ASP.Net 6, Postgresql, Dapper ORM,and deployed on Heroku.

Line graph of stock trends on laptop screen Photo by Nicholas Cappello on Unsplash

Phoenix Rent Predictor

This is a rent prediction web app, based on a machine learning algorithm I created using python and SciKitLearn. The housing data was based on a Kaggle dataset that contained housing and apartment listings from 2020. The average margin of error is from $108-$175 when this model was created in September of 2021. This website was created using Python and the Flask framework, and was powered by the machine learning model. More information can be found on the Github Repo.

Person browsing social media Photo by Austin Distel on Unsplash

Social Media Rest API

This is a social media REST API i built using Fast API. I have been comparing different ways to create APIs, from C#, Node.js, and now Python. I really enjoyed working with FastAPI, and found the name of the framework to be quite apt. It is extremely easy to get a fully fledged CRUD API up and running pretty quickly. Technologies included in building this application was FastAPI, SQLAlchemy, Alembic, JWT Tokens, PostgreSQL, Docker, and Heroku.

Java Appointment Scheduler

Appointment Scheduler

Created and implemented a Java based GUI appointment scheduler that allowed the user to login, create customers and appointments saved to a persistent MySQL database. Appointment times would be displayed on user’s local time zone and compared against business hours based in Eastern Time Zone. Application would detect the user’s system default language and would translate the login screen into French or English if necessary.

Education

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Western Governors University

Bachelors of Science - Computer Science 2021

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Arizona State University

Bachelors of Art - Digital Culture 2013