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TitleDescriptionContent AreaContent TypeTechnology
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NLP FoundationsThis course should introduce core NLP concepts interactively using Python, including tokenization, term frequency (bag-of-words and TF-IDF), embeddings, and named entity recognition (NER). This course should take a modern view of NLP given how LLMs have shifted the space over the last few years. It should focus on core NLP concepts and simple implementations using, for example, nltk, before moving on to pre-trained NLP models available on Hugging Face. In this course, we're not looking to build multi-step NLP pipelines using libraries like spaCy, as these topics are covered in more advanced DataCamp courses for learners interested in diving deeper into NLP. Prior to this course, learners will have familiarity with core Python data structures, control flow, and functions as covered in the course, Python Toolbox, but will have no experience with ML or NLP.Artificial IntelligenceCoursePythonApplication Form
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Cleaning Data in JavaThis two-to-three-chapter course teaches learners essential techniques for cleaning data. Discover techniques for handling common data quality issues including handling missing data through dropping or imputing, convert data into appropriate types, remove duplicates, and transform strings by removing typos and implementing consistent formating.
Prerequisites: Introduction to Importing Data in Java
Emerging CurriculumCourseJavaApplication Form
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