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Introduction to Natural Language Processing

Issued to: Ja'Nya Jenoch

Issued By: Courses

Date Issued: Dec 30, 2025

Description: Course Overview:
This course is designed for beginners through intermediate learners with basic Python understanding and aims to provide a solid foundational introduction to Natural Language Processing (NLP), including an exploration of Generative AI Large Language Models (LLMs). The course will progress starting with the history and basics of NLP and concepts will be presented in clear terms, demystifying NLP jargon. The course will be structured in a modular, asynchronous format, allowing learners to move forward or backward at their own pace and providing the ability to jump to specific topics of interest. The course will provide progressively more complex theoretical, conceptual and hands-on applications in Python in every module as learners advance.

This course will cover the following topics:

Introduction to NLPHistory of NLPComputation of linguistic knowledgeLexical semantics, Syntactic analysis, Semantic analysis and PragmaticsMachine learning for NLPThe Transformer ModelLLMs for NLPLLM tools and APIsLLM Models and trainingApplications of LLMs in the medical domainResearch in NLP and LLMsFuture Directions of Generative AICourse Objectives:
Upon completion of this course, students will be able to:
Understand the basic concepts of NLPDescribe the history of NLPCompute linguistic knowledgeUse lexical semanticsPerform syntactic analysisPerform semantic analysisUnderstand pragmaticsExplain TransformersUse machine learning for NLPUse LLMs for NLPApply LLMs in the medical domainCourse Structure: Module 0: Introduction to NLP and its ApplicationsModule 1: Text Classification and Sentiment Analysis and Named Entity RecognitionModule 2: Introduction to Large Language Models (LLMs)Module 3: LLM Terminology, Techniques and ToolsModule 4: Deployment and Scaling of NLP ModelsModule 5: NLP for Medical Practice and ResearchModule 6: Future Directions and Open Research Problems in NLP

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