How long does it take to complete Getting Started with Natural Language Processing with Python?

The total duration of the course is approximately 1 hour 43 minutes. Since it is generally self-paced, completion time depends entirely on your learning schedule and availability.

Is this course more theory-focused or project-focused?

This course provides a strong mix of conceptual theory and practical application to ensure a comprehensive understanding of the subject matter.

What careers is this course relevant for?

The skills taught in this course are highly relevant for professionals pursuing roles within Data Science and adjacent technical fields looking to upskill.

Data Science

Getting Started with Natural Language Processing with Python

Name: Getting Started with Natural Language Processing with Python
Availability: InStock
Rating: 4 (285 reviews)

This course is all about taking raw text data and deriving insights and value from it--processing text data using standard techniques in Natural Language Processing and Machine Learning.

Beginner FriendlySelf-Paced Learning

Reviews ( 285 )

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🧠 Recommended for beginners

⚠ Not ideal for advanced users

Learning Journey Context

This course serves as an entry point into Data Science, building foundational knowledge before moving on to advanced frameworks or specialized paths.

Career Relevance

Relevant for: Frontend Developer, Full Stack Developer, Web Engineer.

💡This course fits perfectly into our comprehensiveData Science Learning Path. Explore the ecosystem to see how it compares to other foundational skills.

Quick Facts

1 hour 43 minutes

pluralsight

Beginner

Self-Paced Online

Core Courses

pluralsight

English

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What You’ll Learn

Text data is available in abundance on the Internet, whether it be reviews, tweets, surveys, web pages or emails. Natural language processing is a powerful skill that helps you derive immense value from that data. In this course, Getting Started with Natural Language Processing with Python, you'll first learn about using the Natural Language Toolkit to pre-process raw text. Next, you'll learn how to scrape websites for texting using BeautifulSoup, as well as how to auto-summarize text using machine learning. You'll wrap up the course by exploring how to classify text using machine learning. By the end of this course you'll be able to confidently process raw text data and apply machine learning algorithms to it.

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