Full course description
This course, presented in a "Train the Trainer" format, offers participants a comprehensive introduction to the foundational concepts and practical applications of Natural Language Processing (NLP). Participants will explore essential NLP techniques, including data acquisition, storage methods, and preprocessing methods such as document similarity and Word Vectors. The course introduces popular NLP libraries like NLTK, TextBlob, spaCy, and Gensim, as well as data visualization techniques. Learners will also gain hands-on experience with machine learning models, neural language models, and their applications in tasks such as language detection, translation, and sentiment analysis. Additionally, participants will develop Python-based AI projects, create, and deploy chatbots using tools like Chatteron and Heroku, and deepen their understanding of advanced NLP models. By the end of the course, participants will be equipped with the skills and knowledge needed to design and implement robust language recognition and processing applications.