The curriculum emphasises current topics such as sustainable construction, environmental systems, transportation and water-resources, ensuring students are ready for real-world infrastructure challenges.

Yes, students undertake multiple departmental projects, leveraging labs, field work and construction technology modules to apply engineering in practice.

Electives in structural, geotechnical, environmental and transport engineering allow students to tailor their learning and prepare for roles in design firms, consultancy, public works or research.

By integrating courses on smart infrastructure, sustainable materials, environmental systems and project management, the programme equips graduates to lead in tomorrow’s built environment.

Graduates are well-positioned for roles in infrastructure development, consultancy, construction management, urban planning, environmental and water-resource engineering, as well as further study.

By covering aerodynamics, propulsion, and structures alongside engineering design projects, the curriculum mirrors the technical demands of the aerospace sector.

Laboratory sessions, computer-aided design and mechanics workshops give students early exposure to aerospace applications and simulations.

An emphasis on experiential learning, project work and strong foundational sciences ensures graduates possess both breadth and depth of knowledge.

Students are prepared for roles in aircraft design, defence technology, propulsion systems, unmanned aerial vehicles and research institutions.

The project-based framework encourages students to design creative engineering solutions while developing collaboration and leadership skills essential to the industry.

The programme blends classical engineering principles with modern technologies, empowering students to innovate in sustainable design, manufacturing, and advanced materials.

Students experience immersive, hands-on learning in state-of-the-art design and manufacturing labs, supported by expert faculty and real-world industry collaborations.

Through design challenges, multidisciplinary projects, and innovation-led competitions, students learn to turn ideas into practical engineering solutions.

Graduates are equipped for careers across automotive, aerospace, robotics, and energy sectors, with strong analytical and design foundations valued globally.

The emphasis on experiential learning, digital simulation tools, and sustainable engineering practices ensures graduates are not just skilled professionals but responsible innovators.

The programme is designed to build dual expertise, nurturing students who can think mathematically and code computationally. This rare combination enables them to excel in data science, AI, quantitative finance, research, and advanced analytics roles across industries.

This programme is ideal for curious, analytical thinkers who enjoy logic, problem-solving, and exploring how mathematical theory powers modern technology. It develops both conceptual understanding and practical application, preparing students for innovation-led careers.

While traditional computer science focuses primarily on coding, computation & mathematics deepens students’ understanding of the mathematical principles driving algorithms and models. This gives them a strong conceptual edge in high-end computational research and emerging tech domains.

Students engage in research internships, mathematical modelling workshops, and interdisciplinary capstone projects in collaboration with Mahindra University’s research centres and industry partners, offering real-world exposure from early on.

Graduates are well-prepared for careers in data science, operations research, financial analytics, cybersecurity, AI research, and academia. Many also pursue advanced studies at leading international universities.

Our ECM program combines electronics, computer science, and systems engineering in a carefully designed curriculum, giving students the skills and confidence to become future innovators in technology.

Graduates are prepared for careers in embedded systems, IoT, AI, robotics, hardware-software design, and even higher studies or entrepreneurial ventures.

Both. The program ensures students gain strong expertise in electronics and circuits as well as programming, computational theory, and system design.

Our holistic approach includes mentorship, innovation labs, clubs, and leadership opportunities, helping students develop confidence, teamwork, and problem-solving skills.

From dedicated AI and Robotics labs to live industry projects, hackathons, and internships, students actively apply their learning to real-world problems. The programme also includes experiential courses where students design and deploy AI models using contemporary tools and frameworks.

AI students are encouraged to explore research early on through faculty-guided projects, access to specialised centres such as the Mahindra University AI Research Lab, and participation in global AI competitions and conferences. The programme cultivates a strong research mindset alongside technical excellence.

Students can choose electives in areas such as Natural Language Processing, Computer Vision, Reinforcement Learning, and Generative AI, enabling them to tailor their education towards fast-evolving AI domains and industry needs.

Through partnerships with leading tech firms and start-ups, the curriculum stays updated with emerging trends. Guest lectures, mentorships, and collaborative projects ensure students gain direct exposure to industry practices and future-ready.

The project-based framework encourages students to design creative engineering solutions while developing collaboration and leadership skills essential to the industry.

The CSE curriculum is designed around 11 core departmental courses (40 credits) covering algorithms, data structures, databases, cryptography, and machine learning. It blends strong theoretical grounding with application-driven labs and projects, ensuring graduates are industry-ready from day one.

Students can pursue five professional and open electives (15 credits) in areas like High-Performance Computing, Data Mining, Information Security, Graphics, and Embedded Systems, allowing them to tailor their expertise toward emerging technologies.

The CSE programme encourages research from the undergraduate level, with faculty-mentored projects, capstone work, and access to research labs in AI, Robotics, and Computational Systems. Students are guided by Ph.D. faculty from top global institutions.

With a 12:1 student-faculty ratio, fully residential campus, and project-based learning culture, CSE students experience personalized mentorship, vibrant peer learning, and a collaborative atmosphere ideal for growth and innovation.