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What is Natural Language Processing (NLP)? (W7108G)     » zur vollständigen Seminarliste

This course introduces key concepts and methods in Natural Language Processing (NLP), the subfield of data science and artificial intelligence that deals with computer interaction with human language. The course covers 1) The definition of NLP, and its relationship to data science, artificial intelligence, and other subfields therein, 2) Historical thought and development in NLP as well as recent breakthroughs in NLP enabled by artificial intelligence, and 3) Select methods and use cases for NLP, focused mainly on business contexts. The course will also briefly introduce learners to award-winning IBM Watson NLP tools, which make the discussed technologies accessible to non-technical users. Upon completion of the course, learners will feel comfortable describing what NLP is, how it has evolved from historical precedents to contemporary developments, and several specific methods and use cases for NLP technologies in organizational settings. Learners will leave this course well-prepared for more applied and technical courses on NLP.IBM Clients and Sellers - Consider this course as part of an individual or enterprise subscription service:IBM Data/AI Individual Subscription (SUBR003G)IBM Digital Learning Subscription — IBM Data/AI Enterprise Subscription (SUBR004G)IBM Learning Individual Subscription with Red Hat Learning Services (SUBR013G)Alle IBM Trainings werden mit Original IBM Schulungsunterlagen angeboten und finden in Kooperation mit dem von Arrow ECS autorisierten IBM Schulungspartner esciris statt.

Kurs-Id: IBM_W7108G

Seminarinhalt

• Defining NLP 

• NLP History 

• NLP Applications 

• Working With Text 

• From Models to Systems

Informationen
Zielgruppe

The course is intended primarily for learners with a focus on business and/or technology, and specifically those seeking to better understand what NLP is, where it came from, and how it can benefit their organizations. Although the course does not cover the technical aspects of building NLP systems, Data Scientists, Machine Learning Engineers, and other technically-inclined learners may still find concepts and best practices introduced in the subject matter to be useful.

Vorkenntnisse

No prerequisite knowledge is assumed, however a basic understanding of artificial intelligence and machine learning (i.e. what they are, what they do) will be beneficial.

Termine
Hinweis

Das Training findet auf Deutsch statt.