Continuing Education

CCTB252 - Fundamentals of Natural Language Processing

Course Code:  
CCTB252
Campus:  
Online
Prerequisite:
Pre-Requisites: CCTB251

Course Code

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Campus

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Course Overview

Language Models predict words by looking at word probabilities. Therefore, in order to understand how Large Language Models work, it is critical to understand how Natural Language Processing functions. This course will provide an overview of the process of conducting natural language processing, including tokenization, stop words removal, word stemming, and the application of open-sourced BeautifulSoup library for parsing structured data. With the skills you gain in this course, you will be able to reason how Large Language Models could handle tasks such as summarization, translation, and classification under the hood. Using of Natural Language Processing will also expand your knowledge on prominent technologies including ChatGPT, Google Search and Amazon Alexa. You will also gain experience in applying Natural Language Processing to convert human language into a form that machine learning algorithms can understand. It is required that you have experience with Python programming before enrolling in this course.

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Upcoming Offerings

This course is part of these programs or course groups:

Large Language Model


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Delivery Methods

  • Face to Face: Where: In-person meetings. When: Course is scheduled at a specific time for students to attend. Face-to-face instruction at all class meetings. Location may be on campus or at a worksite.
  • Blended: Where: Mixture of in-person & online components. When: Course is scheduled at a specific time for students to attend. Combination of face-to-face and online components at specific times. Some online components may be accessed online anytime.
  • Hyflex: Where: Choice to attend in-person or online meetings. When: Course is scheduled at a specific time for students to attend. For each class, students choose to attend in-person with the instructor or online at a specific time.
  • Remote Live Delivery: Where: Online with instructor. When: Course is scheduled at a specific time for students to attend. Instruction is delivered at set times online. Students do not come to campus.
  • Remote On-Demand Delivery: Where: Online anytime. When: No set class meetings. Coursework is accessed on-demand and online. While there are no set class meetings, there may be set due dates and deadlines for some activities. Students may interact with peers through virtual tools.
  • Remote Independent: Where: Online anytime. When: No set class meetings. Coursework is accessed on-demand and online, with no instructor support. While students choose when to do coursework, there may be set due dates and deadlines. 
  • Work Placement: Where: In-person meetings. When: Work is scheduled at a specific time for students to attend. Onsite work integrated learning. Location at a worksite.
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