Advanced Text Analysis Using Natural Language Processing (10SMDSI_ULM)

Description

This course is designed for beginners who are curious about how to analyze and make sense of large amounts of text data, especially in the field of health research. No previous knowledge in text analysis is required—just an interest in learning new ways to work with data.

In this course, students will explore how to uncover hidden topics in text in data-driven fashion (like finding themes in health articles) using a technique called topic modeling. They will also learn how to create simple tools (called classifiers) that can automatically sort and categorize text into different groups. The course will cover some basic ideas from natural language processing (NLP), which is the engine behind e.g. chatbots and search engines. Throughout the course, students will work with real examples from health research, but are also welcome to bring their own data if they have it.

This course requires students to have basic Python skills, including familiarity with the 'pandas' and 'numpy' libraries for data manipulation. They will also need to set up and be familiar with Jupyter Notebook (https://jupyter.org/) prior to the course.
Please note that there will be no introductory session on Python.