his beginner-focused course on Natural Language Processing (NLP) introduces learners to using spaCy with Python to process and analyze text efficiently. Starting with the fundamentals, students learn how to clean and tokenize text, recognize entities, and perform part-of-speech tagging using spaCy’s powerful tools. The course demonstrates how NLP pipelines work, transforming raw text into structured data for machine learning and AI applications. Learners also explore vector representations, linguistic features, and practical examples to extract meaningful insights from text. By combining theory with hands-on coding exercises, the course enables students to implement NLP tasks such as sentiment analysis, named entity recognition (NER), and text classification. By the end of the course, beginners gain a solid understanding of spaCy’s capabilities, Python integration, and foundational NLP concepts, preparing them for more advanced NLP projects and real-world applications. This course is ideal for anyone starting their journey in NLP, data science, or AI, providing a practical, project-oriented introduction t