What is the eligibility to get admission in IILM Undergraduate College for UG/PG courses?

The Summer School programme at IILM University offers students the chance to choose from a wide range of subjects offered by partner universities, with the flexibility to study additional papers or pursue personal passions such as photography, music, art, or literature. The duration of the summer session typically ranges from 6-10 weeks, allowing students to explore options with prestigious institutions such as Boston University, New York University Stern, University of Berkeley in the USA, and London School of Economics in the UK.

At IILM University Gurugram, the institution offers an MBA programme rather than a PGDM program.
To be eligible for the MBA programme at IILM University, candidates must hold a Bachelor’s degree in any discipline. Additionally, they are required to have achieved a minimum score of 50% in one of the following competitive examinations: CAT, MAT, XAT, CMAT, GMAT, ATMA, or NMAT. The admission process begins with online registration, followed by a profile review. After this, an interview is conducted, and if you pass the interview, you can enroll in the university.

The Post Graduate Diploma in Management (PGDM) in Entrepreneurship and Family Business programme at IILM University is a two-year full-time master's level program.

Students undergo six trimesters, spread over the duration of two years, with the curriculum designed to provide a comprehensive understanding of entrepreneurship, family business management, and related skills.

The program includes a summer internship project and immersion with an incubator and accelerator scheduled at the end of the first year, adding practical experience to the academic learning.

The curriculum for the B.Tech programme includes courses in Computer Architecture, Programming languages, Probability, Statistics, Data Structures, Database Management System, Software Engineering, Data Security, Internet of Things, Computer Networks, Web Development, Artificial Intelligence, Machine Learning, Deep Learning, Optimization Algorithms, Natural Language Processing, and Computer Vision.