TecHno RayZ’s NLP Full Course is a comprehensive series designed to teach learners the core concepts and practical applications of Natural Language Processing. The course begins with an introduction to NLP, discussing its definition, phases, applications, and the common challenges faced while working with human language data.
Early lectures explore ambiguity in language, NLP pipelines, and n-gram language models, giving learners a foundation to understand statistical approaches in NLP. The series then moves into probabilistic models, introducing Hidden Markov Models (HMM) and their application in POS tagging, allowing learners to understand sequential labeling tasks.
Advanced sections focus on parsing techniques, including shallow and deep parsing, top-down and bottom-up parsing, and recursive descent and shift-reduce parsers. Learners also explore constituency and dependency parsing, which are critical for syntactic analysis in NLP. The course concludes with information extraction techniques, enabling learners to extract structured information from unstructured text.
This course is ideal for students, developers, or professionals aiming to build a strong foundation in NLP and implement real-world applications such as chatbots, text summarization, and machine translation. By the end, learners will gain both theoretical knowledge and practical skills to work confidently in NLP projects.
