Natural Language Processing and Knowledge Representation Fundamentals

How do computers make sense of human language? Bridging the gap between human communication and computational logic requires a solid understanding of both linguistic theory and modern data structures. This text-based course guides you through the foundational concepts of natural language processing and computer-based knowledge representation. You will start with core terminology, cognitive principles, and syntax before exploring how to design systems that model meaning. By the end of this course, you will understand how to represent human knowledge in structured formats and apply modern algorithmic approaches to process natural text. What you'll learn: Understand the core linguistic and cognitive principles behind computer language processing; Represent semantic meaning and human knowledge using structured data models; Analyze syntactic structures of sentences using computational parsing techniques; Apply modern vector-based representation and basic tokenization patterns; Design rule-based and statistical systems for text comprehension. The course begins with foundational concepts in linguistics and knowledge modeling, progressing systematically to practical engineering strategies for building language-processing systems. This course is designed for beginners, software developers, and cognitive science enthusiasts with no prior natural language processing experience. Start your journey into the mechanics of computational language today.