This course introduces the foundational concepts of large language models (LLMs) and deep learning techniques for text analysis, a critical skill set in today’s AI-driven landscape. As organizations increasingly rely on intelligent systems to process and interpret language data, understanding these technologies has become essential for modern professionals.

Throughout the course, learners will explore how deep learning models analyze and extract meaning from textual data, gaining practical insights into real-world NLP applications. By studying the architecture and working principles of transformers and LLMs, participants will build the skills needed to apply these technologies to tasks such as text classification, sentiment analysis, and language generation. What sets this course apart is its balance of conceptual clarity and application-focused learning, combining theoretical foundations with examples drawn from modern AI systems. Learners will gain a clear understanding of how cutting-edge models power today’s most advanced language technologies. This course is ideal for aspiring data scientists, AI practitioners, and developers with a basic understanding of programming and machine learning concepts who want to deepen their expertise in NLP and deep learning. This course is part one of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization.