We are proud to announce that our college has once again secured a place in the prestigious NIRF Rankings 2025, in the 201 - 300 band, as recognized by the Ministry of Education (MHRD), Government of India, New Delhi. Congratulations to all staff and students for this remarkable achievement!                    Revised II B.Tech I Semester (AR 23) Mid I Timetable_September 2025                    Tender Notice | AITAM/IDEALAB/2025-26/04 | Sealed tenders invited for supply & installation of Lab Equipment under AICTE IDEA Lab Project. Bid submission: 30-08-2025 to 18-09-2025. Details at 👉 https://aicteidealab.adityatekkali.edu.in | Contact: Dr. G. Sateesh Kumar, 9440347764.                    Results Declared for II Semester MCA Regular (AR 24) examinations, June 2025. Last date to apply for revaluation/recounting is 25th August 2025.                    Results Declared for I B.Tech. II Semester Supplementary ( AR23, AR20, AR18 & AR16) examinations, August 2025. Last date to apply for revaluation/recounting is 25th August 2025.                    Results Declared for II B.Tech. II Semester Supplementary ( AR23, AR20, AR18 & AR16) examinations, July 2025. Last date to apply for revaluation/recounting is 25th August 2025.                    Access the AICTE Web Portal for Student and Faculty Feedback at: https://www.aicte-india.org/feedback/index.php. Click here to provide your valuable feedback.                    AITAM is now NIRF ranking(201-300 band) institution awarded by Union Ministry of Education, Government of India, New Delhi                   
Department of

Vision & Mission

Our Vision

To lead in Data Science education and research, empowering students to innovate, solve problems, and make impactful decisions using data-driven technologies for the benefit of society and industry.

Our Mission

  • Provide a strong foundation in data science for innovative thinking and problem solving
  • Incorporate practical skills in database design, implementation, and decision support systems to enhance business processes
  • Prepare students in creating effective data models, maintain data quality, gain insights, and manage large datasets.