NLP Foundations: Tokenization, Sentiment Analysis, and Neural MT

Natural Language Processing (NLP) powers the technology behind modern search engines, translation tools, and virtual assistants. This text-only course guides you through the foundational concepts and practical workflows needed to process and understand human language using code. By reading through structured explanations and analyzing code snippets, you will transition from understanding basic text preprocessing to comprehending how complex neural machine translation models operate. What you'll learn: Understand core NLP terminology, text preprocessing, and foundational language concepts; Implement modern tokenization strategies including subword tokenization and Byte-Pair Encoding (BPE); Build sentiment analysis workflows to classify text and extract emotional tone; Explore neural machine translation architectures and the role of attention mechanisms; Practice text representation techniques using modern embeddings and vector spaces. The course begins with essential definitions and text processing basics before advancing to sequence-to-sequence concepts and modern neural network applications in translation. Designed for beginners interested in data science and computational linguistics, this course requires no prior NLP experience. Start reading today to unlock the power of language processing.