Somaiya Vidyavihar University B.Tech Admissions 2024
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TNEA 2024 College Predictor
Course | Category | Opening Home State rank | Closing Home State rank |
---|---|---|---|
B.Tech Information Technology | General - | 9032 | 89327 |
BE Agricultural Engineering | General - | 30001 | 82814 |
BE Artificial Intelligence and Data Science | General - | 24401 | 96535 |
BE Computer Science and Engineering | General - | 0 | 0 |
BE Electrical and Electronics Engineering | General - | 74940 | 125915 |
BE Electronics and Communication Engineering | General - | 52881 | 118210 |
BE Mechanical Engineering | General - | 119911 | 139885 |
Every year, Indra Ganesan College of Engineering Tiruchirappalli Publishes new cutoffs. The candidate needs to score at or above the IGCE Tiruchirappalli TNEA Cutoff in order to be admitted in UG programmes. The IGCE Tiruchirappalli Cutoff is determined by a number of variables, including cutoff patterns from prior years, the availability of seats in the institute courses, the number of applicants, the difficulty of the admission exam, and the number of individuals who applied.
Course | Opening Home State rank | Closing Home State rank |
B.Tech Information Technology | 9032 | 89327 |
BE Agricultural Engineering | 30001 | 82814 |
BE Artificial Intelligence and Data Science | 24401 | 96535 |
74940 | 125915 | |
BE Electronics and Communication Engineering | 52881 | 118210 |
119911 | 139885 |
Course | Opening Home State rank | Closing Home State rank |
95700 | 95700 | |
BE Agricultural Engineering | 91688 | 91688 |
102437 | 102437 | |
BE Computer Science and Engineering | 53457 | 53457 |
BE Electronics and Communication Engineering | 119474 | 119474 |
Course | Opening Home State rank | Closing Home State rank |
B.Tech Information Technology | 112496 | 127061 |
115372 | 115372 | |
BE Artificial Intelligence and Data Science | 152079 | 152079 |
BE Computer Science and Engineering | 122758 | 122758 |
151516 | 151516 |
Note: The cut off trends have been calculated as per the inputs from students, historical data and predictive models.
Improved better now compared to when I join. We were the 1st batch so not much infrastructure initially. Now it's good and many buildings there with best amenities. Lab facility is also good and big enough
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