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Course Description

Text mining, often referred to as Natural Language Processing (NLP), is a swiftly expanding field spurred by the progress of Artificial Intelligence (AI). Its primary objective revolves around converting unstructured text into structured knowledge, thereby streamlining data curation and enabling knowledge discovery. The volume of textual data has been growing rapidly. The amount of popular text databases is at a million or trillion scales. As exemplified by the COVID-19 pandemic, LitCovid (https://www.ncbi.nlm.nih.gov/research/coronavirus/) has meticulously tracked around 370,000 articles pertaining to COVID-19, with a monthly influx of approximately 10,000 articles. In such scenarios, text-mining techniques prove indispensable. For instance, the automatic extraction of symptoms, diseases, and drugs mentioned in these articles could assist in diagnosing and managing COVID-19 patients.

Learner Outcomes

When you complete the course successfully, you will be able to:

  • Describe text mining essentials, spanning text preprocessing, text representation methodologies, text modeling techniques, and evaluations
  • Utilize Python and popular libraries such as NLTK, spaCy, scikit-learn, and huggingface 
  • Compare range of cutting-edge text mining applications, including but not limited to named entity recognition, topic modeling, and text summarization, all of which hold immediate applicability across diverse domains
  • Gain an introduction to statistical models of Machine Learning applied to NLP and IR

Microcredential(s):

This course applies toward the Bioinformatics Endeavor digital badge.

What FAES Learners are Saying

"Knowledgeable and friendly instructor eager to help." - FAES Learner

Textbook Information

A textbook is available for this course. 

Click here to view a textbook list for FAES courses and purchasing information. Please note that tuition does not include textbooks.

Prerequisites

Prior exposure to programming and Python is highly recommended, but not required to attend this class. We will provide a crash tutorial on Python in the first week. Learners without experience in programming languages are expected to practice and grasp the basic syntax of Python. There are also plenty of coding exercises to practice throughout the course. If you are unsure that you meet the prerequisite requirements, please contact registrar@faes.org and provide information about your course of interest and background knowledge.

Refund
Follow the link to review FAES Tuition Refund Policy.

Scholarship and Funding

Are you a self-funded student? FAES offers scholarship options. Click here for more information and to apply. 

Looking for resources to help you acquire funding for your continued education? Click here for our funding justification guide. 

Photo Release

By registering for this event, you agree to allow FAES to take photographs of you during the event and to use these photos for promotional purposes, including on our website, social media, and marketing materials, without further compensation. You understand that you have no right to review or approve the final use of these images.

 

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