It is estimated that almost 80% of the world’s data is unstructured text-based data. Because it’s hard to deal with, unstructured data is often skipped over in favor of analyzing structured data (eg, Likert scales). This means we are neglecting a large portion of the world’s data, which could be full of rich, valuable insights. This course will teach you how to start using and understanding text-based data with natural language processing.
You should take this course if:
You are a marketer or data insight professional who would like to learn how to extract better insights out of text data.
You are a marketer or data insight professional and would like to implement predictive models using text data.
You are a marketer or data insight professional and you would like to start learning how to use programming language to analyze data.
Follow a Structured Curriculum
Introduction to python and R
In this section, you’ll learn about the two programming language most data scientists and data insight professional use.
In this section, you’ll learn how to implement basic models to classify text responses. Concrete examples include classifying sentiment and emotion.
Text-based classification
Sequence tagging and sentences
In this section, you’ll learn how to implement models that can predict the probability of the next word based on previous words used.
In this section, you’ll learn how to implement models that can map out latent semantic spaces or the relative meaning of words.
Vector space models and semantics
Ready to Continue your Education?
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