CNLP case studies

The CNLP is a professional certification for practitioners who build, evaluate, and operate natural language processing systems in production. It suits machine learning engineers moving into NLP, data scientists who own text pipelines, and technical leads who need to reason about model behavior, cost, and risk rather than only training accuracy. Candidates typically arrive with working Python, basic statistics, and some exposure to neural networks; the exam tests breadth across the NLP lifecycle rather than the depth of a research specialization. The eight blueprint domains run from linguistic fundamentals and text preprocessing through classical statistical methods, deep learning, and transformer-based large language models, then into evaluation and responsible AI, deployment and MLOps, and applied business use cases. The CNLP case studies are 5 cases and about 3,410 words.