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Python Background for Text Analysis and NLP

Python Background for Text Analysis and NLP In-Person / Online

This workshop focuses on working with strings and text data in Python, building the skills needed for text processing and natural language processing (NLP) tasks. You’ll learn how to manipulate, clean, and transform text data using techniques like regular expressions, stop words, tokenization, and stemming/lemmatizing. This session will help you become comfortable handling text data in Python, laying the groundwork for more advanced work in NLP and document analysis.

Note: This workshop will be offered in person at the UCSF FAMRI Library at Mission Bay and online through UCSF Zoom. You will receive an email from LibCal with room information and Zoom link prior to the start of the workshop. 

 

Workshop Series: Data and Document Analysis with Python, SQL, and AI

This series is designed for researchers, staff, and students who want to learn Python from the ground up, focusing on data analysis, document analysis, and AI-based research. Throughout the workshops, we’ll dive into various data types—including numerical data, health data, text, and images/videos—and explore analysis techniques like regression, classification, and sentiment analysis. We’ll put a particular focus on text analysis, especially analyzing documents from our industry document library.

As programming evolves, so does the way we learn it. While we’ll introduce AI-assisted programming earlier in the series than in past workshop series, we’ll still start with the basics. The early workshops (Intro to Python Parts 1 & 2 and Intro to SQL) will use AI sparingly. As the series moves forward, we’ll dive into topics like web APIs, text analysis, natural language processing, machine learning, regression, document analysis, and AI system interaction, with more AI-driven techniques along the way.
 

 

Date:
Friday, May 23 2025
Time:
9:00am - 11:00am
Time Zone:
Pacific Time - US & Canada (change)
Location:
Virtual
Campus:
Online
Categories:
  Data Science     Data Science > Programming  

Registration is required. There are 20 in-person seats available. There are 36 online seats available.

Event Organizer

Profile photo of Geoffrey Boushey
Geoffrey Boushey