Master of Computer Applications - Generative AI

Master of Computer Applications (MCA) in Generative AI at Alliance University is a specialised postgraduate programme that focuses on the development and application of artificial intelligence techniques to generate new data, content, and solutions. The programme combines core computer science concepts with advanced machine learning and deep learning algorithms, specifically tailored to generative models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and reinforcement learning, making it a premium choice for aspiring innovators.

The MCA in Generative AI is a 2-year postgraduate programme, comprising 4 semesters. The first year shall include subjects like discrete structures, s, Python, advanced data science, UI & UX design for developers, front-end frameworks and technologies, applied statistics, advanced data structures and algorithms, Java object-oriented design and programming, database design and implementation, and graphics design and development. The second year shall include generative models and applications, applied reinforcement learning, deep learning models and applications, computer networks and communications, computer networks and communications, engineering principles of software, NLP algorithms and applications, professional skill development, and internship programmes.

Indeed, internships with AI-focused businesses are the core of the fourth semester. Beginning in their third semester, MCA students establish connections with industry mentors, allowing them to contribute to the advancement of knowledge in their chosen subject.

Indeed. Alliance University extends category-based scholarship programmes to MCA aspirants. Refer to the Scholarships Page for more details.

Master of Computer Applications (MCA) in Generative AI offers hands-on experience through project-based learning, industry mentorship, a dedicated Centre of Excellence (CoE), and industry-aligned workshops. The programme emphasises practical development using generative models like GANs and VAEs, along with agentic AI systems.

The CAN (Career Advancement and Networking) office at Alliance University helps students evaluate their career options, explore new possibilities, guide them on their career choices, prepare them for interviews, and navigate career possibilities for them from a web of job searches. The CAN office facilitates various guest lectures, corporate events, seminars, hands-on training, certificate programmes, workshops, live projects, and industry visits for the MCA students. The University has a high placement rate for MCA graduates with a network of over 1000 recruiting partners.

Yes, research opportunities and publications are encouraged for students in the MCA – Generative AI programme at Alliance University. There is a dedicated research ecosystem that includes research centres, faculties, and a general philosophy that integrates research into teaching and learning. For MCA students, this is primarily facilitated through research-oriented projects that are part of the curriculum.

Graduates of an MCA in Generative AI are prepared for careers as AI Researchers, Generative Model Engineers, Deep Learning Engineers, and AI Application Developers. These roles are in high demand as businesses across various industries leverage generative AI to enhance creativity, optimise processes, and create innovative products and services.

Candidates aspiring for an MCA at Alliance University need to submit an online application. Following the application screening, candidates must take an online aptitude test and then appear in person for an interview. For more details, please view the Admission Process Page.

The programme emphasises practical problem-solving in AI and Machine Learning through high-tech lab facilities, ensuring hands-on experience for students. Makerspace lab offers access to 3D printers, CNC machining, IoT kits, and embedded computers, fostering hands-on experimentation and creation. The AU-TBI provides a supportive environment for innovation, offering access to resources and services for incubation in areas including AI and ML. Also, the Centres of Excellence, Computer Vision and Robotics, serve as hubs for cutting-edge research and innovation in related AI fields.

The programme fee for MCA in Gen AI at Alliance University is Rs. 5 lakhs for a period of 2 years, payable in two instalments. For further details, you can refer to the Fee Structure Page. Hostel fee shall be additional. For more details regarding the hostel fees, you can view the Hostel Fee Structure Page.

The scope of a Master of Computer Applications (MCA) in Generative AI is expansive, offering high-demand careers in cutting-edge fields like AI Development, Machine Learning Engineering, Data Science, and Generative Model Engineering, all focused on creating new content and solutions. Domains in technology, finance, healthcare, and retail are actively hiring skilled professionals to implement generative AI for enhanced creativity, optimised processes, and new products.

Students pursuing MCA in Gen AI at Alliance University gain a comprehensive range of skills that combine core computer science fundamentals with advanced, specialised knowledge in artificial intelligence. The programme emphasises both theoretical foundations and practical application to prepare students for the rapidly evolving AI industry. The technical skills include generative models, large language models, deep learning, machine learning and data science, natural language processing, programming proficiency, data structures and algorithms, software and application development, cloud computing, and ethical AI practices. The core and soft skills include algorithmic and mathematical thinking, problem-solving, creativity and innovation, communication and collaboration, project-based learning, and research aptitude.

The curriculum of MCA in Gen AI includes generative models and their applications, allowing students to focus on core technologies for creating chatbots and image generators. The generative models like generative adversarial networks (GANs), students can generate new images and other creative content. Combining skills from NLP, deep learning, and software engineering allows students to develop advanced virtual assistants capable of natural conversation and performing complex tasks.