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Data and AI

Natural Language Processing

Build practical understanding of text representation, classification, extraction, generation, and language-model evaluation, then use it for building systems that analyze or generate human language.

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Level
Beginner to advanced foundations
Subject area
Data and AI
Learning outcomes
4 focused outcomes

Topic overview

Learn the foundations of Natural Language Processing.

Natural Language Processing connects text representation, classification, extraction, generation, and language-model evaluation with practical decisions and tasks. Guided examples, comparison, practice, and feedback help learners apply these ideas to building systems that analyze or generate human language. The goal is to make each step easier to explain, check, and improve.

Learning outcomes for Natural Language Processing

  1. 1

    Explain the main ideas and vocabulary involved in text representation, classification, extraction, generation, and language-model evaluation

  2. 2

    Follow a repeatable process for building systems that analyze or generate human language

  3. 3

    Compare examples, identify common mistakes, and improve an approach

  4. 4

    Complete an independent natural language processing task and reflect on the result

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Suggested route

How to learn Natural Language Processing step by step.

01

Build the foundation

Explain the main ideas and vocabulary involved in text representation, classification, extraction, generation, and language-model evaluation

02

Practise with feedback

Follow a repeatable process for building systems that analyze or generate human language

03

Practise with feedback

Compare examples, identify common mistakes, and improve an approach

04

Apply and reflect

Complete an independent natural language processing task and reflect on the result

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