The importance of natural language processing technology is increasing as media technology evolves and natural interaction with humans is required. In this course, starting from the basic language attributes, the characteristics of the Korean language will be studied. On the basis of this, conversion of texts into a numeric form which is called language embedding and various applications using it will be learned. In order to develop skills to implement AI software using natural language processing, students first learn the text pre-processing required for cleaning and polishing the documents before language processing is executed. Then, they learn Morphological Analyzers needed to embed words in the smallest semantic unit, word embedding algorithms such as word2vec or fastText, and doc2vec or BERT for a sentence or document embedding. Application of language processing such as sentiment analysis, document classification, translation, and social data analysis will be implemented with deep learning. Speech to Text (STT) that converts speech to text will be also studied tp develop a skill to implement a more practical application.