You can see a list of my articles and projects relating to Python below!

Cleaning and Working with DataFrames in Python

My course is available to watch on Pluralsight!

Using Comet ML for Experiment Management

New tools are coming out every day that can make our work easier within the fields of Data Science, Machine Learning, and AI. Comet ML is a promising tool that offers a platform with several helpful features, one being experiment management.

GitLab CI/CD for Posit Connect

Posit Connect is a service offered by Posit, formally named Rstudio, and is designed to make the delivery of data-driven applications (i.e., dashboards, notebooks, APIs, etc.) fast, approachable, and secure. This article shows how to publish applications to Posit Connect using GitLab CI/CD pipelines.

Streamlit is a popular and powerful Python framework for creating dashboards and data-enabled web apps. I participated in a hackathon back in April 2023 and demonstrated my project A dynamic dashboard for visualizing a user's Skill IQ data. This demonstration showcased my own learning journey as I used Skill IQ to track my proficiency in AWS tooling.

Don't be afraid to approach how you learn Python in a variety of ways. 

Details on the IDEs and package/dependency management tools I use when developing in Python.

Amongst the thousands of modules and packages for the Python language, here I share the ones you should first learn, along with some of my personal favorite.

This article shares important context on some of the fundamentals of Python. I recommend coming to understand these concepts right away when you start learning, such as functions, classes, data types & structures, and modules & packages.

Released back in 1994 by Guido van Rossum, Python is now the most popular programming language in the world. 

Python is the most popular programming language in the world. This article is for beginners who want a comprehensive overview of the language to help get them started.

I led a team of engineers through a three-day hackathon. We developed a POC of a public-facing API using various technologies, specifically Python, FastAPI, Docker, and Snowflake. We presented our results to the company at the end of the hackathon.

As a pet project, I built a system using Airflow, Docker, Python, and an AWS S3 bucket to monitor and track Bitcoin price fluctuations. When scheduled, the Airflow DAG file_to_S3 (1) hits the coinbase API every five minutes, (2) writes the results into an AWS S3 bucket, and (3) sends a confirmation to my personal email.