Python

John Louis-Strakes Lopez

Postdoctoral Scholar
Berkeley School of Education

John Louis-Strakes Lopez is a Data Science Education postdoctoral scholar. He recently received his PhD in Education from University of Caifornia, Irvine. John’s work looks at student epistemological development within data science contexts. He is also interested in designing -and studying artificial intelligence and playful learning technologies for learning. John serves as a co-chair for the International Learning Sciences Student Association.

Beyond work, you will find John reading at a local coffee shop or eating a warm bowl of Pho.

In Silico Approach to Mining Viral Sequences from Bulk RNA-Seq Data

October 28, 2025
by Carly Karrick. Viruses play important roles in evolution and influence ecosystems and host health. However, isolating and studying them can be difficult. In lieu of using resource-intensive methods to concentrate viruses into a “virome,” bulk sequencing methods include data from all biological entities present in a sample. In this tutorial, we explore an approach to mine viral sequences from publicly available bulk RNA-Seq data. The output from this analysis paves the way for future statistical analyses comparing viral communities in different contexts. This approach can be applied to other datasets, including studies of human health.

Pratik Sachdeva, Ph.D.

Research Scientist

I am a Research and Data Scientist in the D-Lab at UC Berkeley. My research focuses on the societal impacts of machine learning models, with an emphasis on understanding the norms and values elicited from large language models. I also lead and support a range of social science projects, spanning hate speech detection, education, and computational humanities. Lastly, I help provide D-Lab's core instructional and consulting services.

I previously obtained my PhD in the Physics Department at UC Berkeley, conducting research in...

Python Introduction to Machine Learning: Parts 1-2

October 21, 2021, 1:00pm
This workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets. No theory instruction will be provided.

Python Visualization

September 30, 2021, 10:00am
For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter notebook.

Python Visualization

October 22, 2021, 10:00am
For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter notebook.

Python Data Wrangling and Manipulation with Pandas

October 19, 2021, 10:00am
Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python. In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

Python Fundamentals: Parts 1-4

August 19, 2021, 1:00pm
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Python Fundamentals: Parts 1-4

October 4, 2021, 12:00pm
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Python Introduction to Machine Learning: Parts 1-2

September 27, 2021, 2:00pm
This workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets. No theory instruction will be provided.