The objective is to introduce the fundamental concepts of artificial intelligence and its applications in music production; to enable students to generate audio samples—using tools such as Suno, Eita, and similar platforms—based on text and musical prompts, to refine the production process incrementally, and to evaluate the resulting outputs in the context of religious music (mûsiki) regarding its text, *makam* (melodic mode), *usul* (rhythmic cycle), prosody, and performance characteristics; and to foster an understanding of the possibilities, limitations, and ethical dimensions that these tools offer for educational and creative endeavors.

The concepts of artificial intelligence, machine learning, deep learning, and generative AI are explored, alongside the underlying logic of how AI functions in music production and the role of human guidance. Music generation tools—such as Suno, Eita, and others—are examined through practical application, covering their interfaces, fundamental usage steps, and available production options. Exercises include prompt engineering, lyric preparation, specifying vocal and instrumental preferences, defining musical structure, generating alternative samples, and refining results through comparison. The generated samples are evaluated based on criteria such as pronunciation, prosody, melodic coherence, *makam* (melodic mode), *usul* (rhythmic cycle), and alignment with the stylistic conventions of religious music. Furthermore, topics such as copyright, consent regarding the use of voice, the disclosure of AI-generated content, and academic integrity are discussed.