Text Analytics 1: Introduction to Natural Language Processing

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27.00 ساعة تعليمية
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Introducing Natural Language Processing is part one of the Text Analytics with Python professional certificate (or you can study it as a stand-alone course). This first course introduces the core techniques of natural language processing (NLP) and computational linguistics. But we introduce these techniques from data science alongside the cognitive science that makes them possible.

How can we make sense out of the incredible amount of knowledge that has been stored as text data? This course is a practical and scientific introduction to natural language processing. That means you’ll learn how it works and why it works at the same time.

On the practical side, you’ll learn how to actually do an analysis in Python: creating pipelines for text classification and text similarity that use machine learning. These pipelines are automated workflows that go all the way from data collection to visualization. You’ll learn to use Python packages like pandas, scikit-learn, and tensorflow.

On the scientific side, you’ll learn what it means to understand language computationally. Artificial intelligence and humans don’t view documents in the same way. Sometimes AI sees patterns that are invisible to us. But other times AI can miss the obvious. We have to understand the limits of a computational approach to language and the ethical guidelines for applying it to real-world problems. For example, we can identify individuals from their tweets. But we could never predict future criminal behaviour using social media.

This course will cover topics you may have heard of, like text processing, text mining, sentiment analysis, and topic modeling.

المدربين

Jonathan Dunn
Jonathan Dunn

I'm a computational linguist, teaching both linguistics and natural language processing. My research models the emergence of grammar within individual speakers and the diffusion of dialects across global populations."

Tom Coupe
Tom Coupe

My research covers a wide range of topics (recent topics include replications, job insecurity, the Eurovision Song Contest, trade policy preferences, football, terrorism, war and happiness). In my papers I typically analyze interesting datasets using econometric methods.

Jeanette King
Jeanette King

I have published widely in areas relating to the Māori language and languages spoken by Māori - from aspects of linguistic change, particularly in the phrasal lexicon, through to language revitalization. I am a member of the MAONZE (Māori and New Zealand English) project examining change over time in the pronunciation of Māori.

I lead the bilingualism theme at the New Zealand Institute of Language, Brain and Behaviour (NZILBB) at UC where my current research includes work on non-verbal behaviour of Māori and Pākehā in New Zealand. Another project, entitled Tuhinga Māhorahora, collects and analyses writing by children in Māori immersion schooling in order to provide feedback to teachers about the use of Māori by their students.

Girish Prayag
Girish Prayag

The overarching focus of my research is consumption experiences in the services industry with a particular focus on the airline, tourism and hospitality industries. My past and current research themes include: consumption emotions, place/brand attachment, anthropomorphism, service design, destination marketing and tourism/event impacts.