In this chapter, natural language processing (NLP) and sentiment analysis are introduced by defining their key concepts, exploring their historical evolution, and explaining how they complement each other. Various types, architectures, and tools used in these fields are examined, with a focus on their advantages, limitations, and practical applications. Future challenges and emerging trends in NLP and sentiment analysis are also discussed. The second part of the chapter provides hands-on experience using R for text and sentiment analysis, covering data preparation, cleaning, and visualization of the most frequently occurring words, along with the creation of a word cloud to effectively represent the processed data.