What are the eligibility criteria for BCA in Artificial Learning & Machine Learning (AL-ML) at Lingaya's Vidyapeeth?
The eligibility criteria for enrolling in the BCA in Artificial Learning & Machine Learning (AL-ML) program at Lingaya's Vidyapeeth require candidates to have completed their 10+2 or equivalent examination from a recognized board with Mathematics or Computer Science as one of the subjects.
What is the fee structure for the BCA in AL-ML program at Lingaya's Vidyapeeth?
The fee structure for the BCA in Artificial Learning & Machine Learning (AL-ML) program at Lingaya's Vidyapeeth is subject to change annually. Prospective students are advised to check the official website or contact the admissions office for the most current fee details.
How does the selection process work for the BCA in AL-ML program at Lingaya's Vidyapeeth?
The selection process for the BCA in AL-ML program at Lingaya's Vidyapeeth typically involves a review of the applicant's academic records, performance in qualifying examinations, and any other criteria as specified by the university. The university may also conduct interviews or entrance tests as part of the selection process.
Is there a cut-off mark for admission into the BCA in AL-ML program at Lingaya's Vidyapeeth?
Yes, there is a cut-off mark for admission into the BCA in AL-ML program at Lingaya's Vidyapeeth. The cut-off mark is determined based on the overall performance of applicants and the number of available seats. It varies each year depending on the applicant pool and is published during the admission period.
What are the placement opportunities for graduates of the BCA in AL-ML program at Lingaya's Vidyapeeth?
Graduates of the BCA in Artificial Learning & Machine Learning (AL-ML) program at Lingaya's Vidyapeeth have various placement opportunities in the tech industry. The university has a dedicated placement cell that works closely with leading companies in the IT and tech sectors to organize campus interviews and placement drives. Past graduates have secured positions in areas such as data analysis, machine learning engineering, software development, and AI research.