The transformation of natural language queries to deterministic finite automata (DFAs) represents a significant advancement in computational linguistics and formal language theory. This study introduces an intelligent system to improve the way users learn concepts related to DFAs. The system extracts relevant keywords from queries, to generate regular expressions by mapping the text to predefined templates. These regular expressions are transformed into DFAs using the syntax tree algorithm. The process of DFA construction is intuitively explained using gpt-3.5-turbo making it easier for users to understand. This system achieves high accuracy for queries that occur frequently in academic curriculum, making it particularly suitable for students, and educators, improving learning outcomes in computer science.