Question: How is the course curriculum for B.E. / B.Tech at Lloyd Institute of Engineering and Technology?

The semester exam results at Lloyd Institute of Engineering and Technology (LIET), Greater Noida, are typically declared within 4–6 weeks after the exams conclude. For AKTU-affiliated exams, results are announced on the university portal (aktu.ac.in) and may take 6–8 weeks. Autonomous semester results (if applicable) are published on LIET's official website.

The CBSE Class 12 results for the current academic year (2024) are expected to be declared by the last week of May 2024, based on recent trends. For the most accurate and official date, regularly check the CBSE website (cbse.gov.in) or official CBSE notifications.

Overall the faculty at Lloyd Institute of Enginnering anf Technology is quite good. They are well qualified and dedicated, supportive and try to provide the students with practical knowledge. LIET's faculty is considered a strength of the institution, contributing positively to its academic environment.

Lloyd Institute of Engineering and Technology (LIET), Greater Noida, has a competent faculty with a balanced mix of experienced academicians and industry professionals. Many senior faculty members in core branches (like CSE, Mechanical, and ECE) hold Ph.D. degrees and have 10+ years of teaching/research experience, ensuring strong foundational knowledge. The institute emphasizes practical, industry-aligned training, with some professors maintaining active corporate collaborations for real-world exposure.

The faculty at Lloyd Institute of Engineering and Technology (LIET), Greater Noida, offers a balanced mix of experienced educators and industry professionals, particularly strong in core engineering disciplines like CSE and Mechanical. While senior faculty members with PhD qualifications and 10+ years of experience provide solid academic grounding, the institute also emphasizes practical, industry-relevant training through collaborations with local firms. However, newer specializations such as AI/ML may lack depth in faculty expertise.