JMI Introduces New Self-financed M.Tech and B.Tech Courses

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Jamia Millia Islamia has introduced new self-financed programs in B.Tech and M.Tech. The B.Tech programs, which include Electrical and Computer Engineering, Electronics (with a focus on VLSI design and Technology), and Computer Science and Engineering (emphasizing Data Sciences), will admit students based on their final rankings in the JEE Main. Additionally, the M.Tech program in Data Sciences is part of the offerings. The annual fee for these self-financed programs is Rs 1,50,000 for B.Tech and Rs 54,000 for M.Tech. Interested candidates can access application forms on Jamia Millia Islamia’s official website,

Jamia Millia Islamia has introduced self-financed programs, with an annual fee of Rs 1,50,000 for B.Tech and Rs 54,000 for M.Tech. Application forms can be accessed on the official website, For courses with admission tests conducted by JEE, online application forms will be available 10 days after the respective agencies declare results. The B.Tech program in Electrical and Computer Engineering aims to produce skilled engineers capable of enhancing the security and robustness of computing systems, especially in communication networks, and advancing the efficiency of cyber-physical systems such as smart grids and autonomous mobile systems.

Similarly, the B.Tech program in Electronics (VLSI Design and Technology) aims to train students in this strategic field, preparing them to tackle the challenge of designing and manufacturing innovative nanoelectronics devices and chips in India. The curriculum aligns with industry requirements in IC and chip design, on par with reputed institutes in India and abroad. The B.Tech program in Computer Science and Engineering (Data Sciences) offers a comprehensive curriculum covering essential topics such as programming languages, algorithms, database systems, data mining, statistical analysis, and machine learning. The M.Tech program in Data Sciences is a postgraduate program focused on advanced studies in Data Sciences, integrating elements of computer science, statistics, and domain-specific knowledge to extract insights and knowledge from data.