Natural Language Processing with Neural Networks

Processing written text with neural networks powers modern search engines, automatic translation, and conversational assistants. This text-based course provides a clear entry point into Natural Language Processing, helping you build practical skills in text representation, neural architectures, and semantic applications. What you will learn: Understand foundational NLP terminology, text tokenization, and preprocessing; Master text vectorization and semantic search using vector embeddings; Explore sequence modeling with recurrent architectures and transformers; Examine chatbot design and conversational AI structures; Apply Retrieval-Augmented Generation concepts to query domain knowledge bases; Practice prompt engineering techniques for language models. You will begin by learning key terminology and foundational text analysis concepts before moving into neural network approaches, vector spaces, and modern text workflows. This course is built for beginners in computer science and data analysis who want a clear introduction to text processing without complex prerequisites. Gain a solid foundation in modern NLP and start reading today.