Text Analytics 1: Introduction to Natural Language Processing

Resumen

Introducing Natural Language Processing, the initial segment of the Text Analytics with Python professional certificate series, offers a deep dive into the foundational elements of natural language processing (NLP) and computational linguistics, accessible either as part of the series or a standalone course. Designed to marry the principles of data science with the underpinnings of cognitive science, this course demystifies the processes enabling computers to comprehend human language.

Exploring the vast ocean of text data, this course serves as both a theoretical and practical guide to natural language processing.

It ensures learners grasp not only the 'how' but also the 'why' behind NLP's operational mechanisms.

In terms of application, participants will gain hands-on experience in conducting Python-based analyses, developing text classification and similarity pipelines employing machine learning. These pipelines span the full spectrum of processes from data collection to visualization, leveraging Python packages such as pandas, scikit-learn, and tensorflow.

The course also addresses the computational understanding of language, contrasting how artificial intelligence and humans interpret documents.

It explores the limitations and ethical considerations inherent in applying computational linguistics to real-world issues, debunking myths such as the potential for predicting criminal behavior from social media profiles.

Key topics include text processing, text mining, sentiment analysis, and topic modeling, among others, making this course a comprehensive introduction to natural language processing.

Provided by edX, this course falls under the categories of Python Courses and Natural Language Processing (NLP) Courses.

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Impartido por

Jonathan Dunn, Tom Coupe, Jeanette King and Girish Prayag

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Materias