Edward Kwartler

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University of St.Gallen
Harvard University Extension School

Course location

University of St.Gallen

Home university

Harvard University Extension School
ted
Ted Kwartler is the VP, Trusted AI at DataRobot. At DataRobot, Ted sets product strategy for explainable and ethical uses of data technology in the company’s application. Ted brings unique insights and experience utilizing data, natural language processing, business acumen and ethics to his current and previous positions at Liberty Mutual Insurance and Amazon. In addition to having 4 DataCamp courses, he teaches graduate courses at the Harvard Extension School and is the author of multiple textbooks including Text Mining in Practice with R, Sports Analytics in Practice with R and Applied Sport Business Analytics. Ted was appointed to a Congressionally mandated 2-year advisorship within the US Government’s Bureau of Economic Affairs called the “Advisory Committee for Data for Evidence Building” advocating for data-driven policies. Ted holds an MBA from the University of Notre Dame (USA) with a concentration in Marketing Analytics.

Courses taught by this instructor

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Natural Language Processing with Bag of Words & LLM Methods

The Introduction to Natural Language Processing (NLP) at GSERM is a comprehensive journey into the world of textual data analysis. The course is designed to immerse attendees in both the theory and practical implementation of versatile NLP methods, transforming qualitative research prospects. Through a mix of lectures and labs, participants will gain practical proficiency in powerful NLP techniques that include: • Large Language Models (LLMs) • Prompt Engineering • Vector Database Basics • Bag-of-words Analysis • Sentiment Analysis • Document Classification and Clustering Students with previous experience in programming, graduate-level statistics, and mathematical theory will benefit most from this course. However, the curriculum is crafted to appeal and be accessible to all researchers eager to integrate NLP tools in their analysis.
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M

2025

Natural Language Processing with Bag of Words & LLM Methods

The Introduction to Natural Language Processing (NLP) at GSERM is a comprehensive journey into the world of textual data analysis. The course is designed to immerse attendees in both the theory and practical implementation of versatile NLP methods, transforming qualitative research prospects. Through a mix of lectures and labs, participants will gain practical proficiency in powerful NLP techniques that include: • Large Language Models (LLMs) • Prompt Engineering • Vector Database Basics • Bag-of-words Analysis • Sentiment Analysis • Document Classification and Clustering Students with previous experience in programming, graduate-level statistics, and mathematical theory will benefit most from this course. However, the curriculum is crafted to appeal and be accessible to all researchers eager to integrate NLP tools in their analysis.
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