3 Courses Required

Target Audience

  • Data scientists
  • Computer scientists
  • Analysts
  • User behavior and UX teams
  • Researchers
  • Social scientists

Accreditation

  • Text Analysis Certificate from Cornell’s Ann S. Bowers College of Computing and Information Science
  • 48 Professional Development Hours (4.8 CEUs)

Certificate Description

In today's AI-driven landscape, processing and analyzing textual data is increasingly critical for understanding customer sentiment, market trends, and other key business insights. Natural language processing (NLP) techniques have become essential tools for transforming raw text into meaningful data that underpins many of today’s AI applications.

This certificate program is designed to equip you with foundational skills in NLP, with a focus on text preprocessing, summarization, visualization, and sentiment analysis. In the first course, you will clean and manipulate text data using regular expressions, preprocess complex textual information, and address common challenges in messy datasets. You will also have the opportunity to explore advanced text preprocessing techniques such as stemming and tokenization, which are essential for preparing text for further analysis. In the second course, you will develop the ability to summarize and visualize text distributions across documents, leveraging tools like word clouds and document-term matrices to uncover patterns and trends. Finally, the third course introduces you to sentiment analysis, where you will quantify and interpret emotions in text and compare sentiment across documents and over time.

By the end of this program, you will have the practical knowledge needed to preprocess and analyze textual data, giving you a valuable edge in data science, AI engineering, or any field that requires a deep understanding of textual information.

To succeed in this program, you should have a foundation in R programming. If you do not have this experience, start with the Data Science Essentials certificate program.

The courses in this certificate program are required to be completed in the order that they appear.

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