Text Analytics with Python - Ubbergo

Text Analytics with Python

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- 10%

£317.00

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Course type

Level

Beginner

Time/Effort

3 months at 3-6 hrs/week

Created by

University of Canterbury

Provider

Session type

Self-paced

Pricing

Instalments

No

Certificate

Available

Projects

Yes

Tutor support

Yes

Access

Course lifetime

More features

Coaching and mentoring, Discounts for eligible learners, Discussions forums, Flexible learning program, Graded assignments

Language

English

Subtitles

English

Skills Covered: Text Analytics, Text Data, Text Classification, Natural Language Processing with Python, Visualizing Text Analytics, Text Similarity, Visualizing Text Analytics, Applying Text Analytics, Computational Linguistics, Statistical Significance Testing

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ABOUT THIS PROFESSIONAL CERTIFICATION


Learn the core techniques of text analytics and natural language processing (NLP) while discovering the cognitive science that makes it possible in this certificate Text Analytics with Python. On the practical side, you’ll learn how to actually do an analysis in Python: creating pipelines for text classification and text similarity using machine learning. These pipelines are automated workflows that go all the way from data collection to visualization. On the scientific side, you’ll learn what it means to understand language computationally. Artificial intelligence and humans don’t view text documents in the same way. Sometimes deep learning sees patterns that are invisible to us. But often deep learning misses the obvious. We have to understand the limits of a computational approach to language together with the ethical requirements that guide how we choose what data to use and how we protect the privacy of individuals.

Along the way, you’ll explore real-world case studies using pandas, numpy, scikit-learn, tensorflow, matplotlib, seaborn, gensim, and spacy within jupyter notebooks to gain useful insights from unstructured data.

 

WHAT YOU WILL LEARN


  • Construct applications using unstructured data like news articles and tweets.
  • Apply machine learning classifiers to categorize documents by content and author.
  • Practice using document similarity and topic models to work with large data sets.
  • Visualize and interpret text analytics, including statistical significance testing.
  • Assess the scientific and ethical foundations of new applications for text analysis.

 

JOB OVERVIEW


  • Unstructured data analysis is an increasingly important part of data science and many analysts will benefit from the techniques introduced in these courses.
  • Digital media roles often work with text analytics as part of the process of marketing, understanding consumer opinions and behaviours from documents.
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Text Analytics with Python
Text Analytics with Python

£317.00

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