NLP Fundamentals Micro-Credential

NLP Fundamentals Micro-Credential

Duration: 3-4 Hours

Description

This micro-credential provides a practical foundation for understanding how computers process and interpret human language. Participants learn key NLP concepts, explore vectorization and sentiment analysis, and gain experience with advanced techniques such as named entity recognition and transformers. Hands-on labs guide learners through building a sentiment analyzer and applying text-processing workflows.

Audience

The intended audience are developers new to the world of NLP who want a practical introduction to its core concepts and techniques. Prior experience with a programming language (like Python) is required.

Objectives

  • Define the core tasks of NLP and why it’s a challenging field.
  • Implement fundamental NLP techniques such as tokenization and stemming.
  • Understand the basics of text classification and sentiment analysis.
  • Use a popular NLP library to build a simple text processing application.
  • Begin to understand how more advanced models like Transformers work.

Prerequisites

Basic programming experience, preferably in Python, and a general understanding of data handling are recommended. No prior NLP or machine learning background is required, making this program accessible to developers, analysts, and data enthusiasts eager to work with text-based data.

Course Outline

Module 1: The Building Blocks of Language

  • What is NLP?
  • The Challenges of Human Language
  • Processing Text
  • Lab – Process a Block of Text

Module 2: Extracting Meaning from Text

  • Vectorization
  • Text Classification
  • Sentiment Analysis
  • Lab – Build a Sentiment Analyzer

Module 3: Beyond the Basics

  • Named Entity Recognition (NER)
  • Word Embeddings
  • Language Models and Transformers
  • Advanced Topics