Brain-Computer Interface (BCI) systems require the usage of datasets corresponding to the spoken languages of patients in order to serve them with neurodegenerative illnesses.There exist a shortage of such BCI datasets for Indian langauges. The primary objective of this endeavor is to provide BCI datasets for Telugu, a prominent Indian language that is spoken by over 90 million people.This dataset includes male and female Telugu language BCI data. The goal of this dataset is to aid in the advancement of BCI research for native Telugu speakers. Using machine learning (ML) and other classifiers, BCI systems can interpret and categorize EEG data into the display or pronunciation of Telugu words. We have recorded 100 distinct Telugu words with ten trials each in both vocal and subvocal forms, along with their equivalent English translations. Increasing the applicability of BCI technology for Telugu speakers is the aim of the IIST-BCI Dataset for Telugu. By encouraging further developments in BCI application research, this dataset enhances the support given to Telugu-speaking patients afflicted with neurological diseases.