This course is designed to help learners master the core architecture of modern natural language processing by building and evaluating transformer-based pipelines from the ground up. Learners will begin by exploring the essential mechanics of tokenization, embeddings, and encoding, learning how techniques like WordPiece transform raw text into high-dimensional representations for tasks such as sentiment analysis and content categorization. Beyond construction, this course emphasizes the critical role of rigorous model assessment. Learners will implement industry-standard automated metrics like ROUGE while simultaneously developing structured human-in-the-loop evaluation strategies to identify subtle issues in safety, toxicity, and alignment. By connecting these technical skills to real-world applications—including customer support automation, social listening, and search optimization—learners will be able to navigate the complex tradeoffs between computational speed and human-verified quality. The experience culminates in a hands-on project where learners will deploy a functional pipeline and produce a professional evaluation summary, ensuring they can deliver reliable, production-ready NLP solutions that meet both technical benchmarks and specific business goals.