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Introduction to Text Analytics with Python

As a universal programming language Python is used in a huge variety of application domains and is often used in data analysis tasks. For the analysis of textual data and especially in the interdisciplinary field of Natural Language Processing (NLP), Python is a very powerful tool.

NLP lies at the intersection of computational linguistics and artificial intelligence. It is an increasingly used domain as NLP enables computers to understand human languages and retrieve meaning from their analysis. Applications of NLP can be found in Machine Translation, Sentiment Analysis, Chatbots, Intelligent Systems, Spell Checking, Predictive Typing, Grammar correction etc.

In this introductory course, students will explore the basics of text analytics and NLP with the powerful Python package Natural Language Toolkit (NLTK) and in parts with spaCy. The course content is disseminated over 9 hours through slides, live coding of the instructor and in-class exercises in individual & pair work.

Learning Objectives
By the end of the introductory course, students will be able to
  • work with different file types in Python.
  • apply text pre-processing techniques for cleaning and preparing textual data.
  • extract information from textual data.
  • perform semantic and sentiment analysis.

Learning Contents
  • Writing and running Python in iPython/Anaconda
  • Opening, reading, writing, and closing files in Python
  • Text pre-processing (Tokenization, Normalization, Stemming, Lemmatization)
  • Part of speech tagging (PoS), Chunking-Named entity recognition (NER) -N-gram Models-Dependency parsing
  • Semantic relations and sentiment analysis

Voraussetzungen

It is necessary to attend "APPB – Python Basics". You should feel comfortable working with control structures, simple functions, and different data types in Python.

Teilnehmende

This introductory course is directed for beginners and is suitable for anyone who wishes to analyze text in Python and gain a basic understanding of Natural Language Processing (NLP).

Durchführung

Kurs APPT 1
Freie Plätze:1
Dauer:3 Tag(e) / 9 Stunde(n)
Kursleitende:Maria Tsilimos
Teilnehmerzahl:Min: 7
Max: 25
Ort:Anmeldung auf der Kollaborationsplattform Teams mit Ihrem UZH Account. Im Team "ZI - IT Fort- und Weiterbildungen" finden sie den Kanal Y01-F-49, ihren virtuellen Kursraum für diesen Kurs.
Y01F49 (on Teams)
Datum/Zeit:
Donnerstag, 28. Oktober 202109:00 - 12:00
Donnerstag, 4. November 202109:00 - 12:00
Donnerstag, 11. November 202109:00 - 12:00
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