Bachelor of Computer Applications - Artificial Intelligence & Machine Learning (AI & ML) ( AI & ML)

The Bachelor of Computer Applications with Specialization in Artificial Intelligence and Machine Learning (BCA – AI&ML) program at REVA University is a comprehensive Four-year undergraduate course designed to equip students with cutting-edge skills in Computer Science, Artificial Intelligence, and Machine Learning Technologies. The 4th Year Honours and Honours with Research tracks offer enhanced opportunities for academic excellence, advanced research, and advanced learning in the specialization areas of Artificial Intelligence and Machine Learning Technologies. With a focus on interdisciplinary learning, experiential learning methodologies, and industry-relevant projects, these programs seek to instil critical thinking, problem-solving abilities, and effective communication skills in students. The curriculum also includes hands-on labs, industry projects, and case studies to ensure practical, experiential learning.

Graduates from REVA University’s BCA - Artificial Intelligence (AI) and Machine Learning (ML) program are well-equipped for a variety of dynamic career paths across the tech industry. Key roles include Machine Learning Engineer, Data Scientist, AI Engineer, Business Intelligence Developer, and Big Data Engineer. These positions leverage skills in Python, deep learning, neural networks, cloud computing, and data analytics—core competencies emphasized in REVA’s curriculum.

The program also prepares students for specialized roles such as Research Scientist, focusing on areas like natural language processing, computer vision, and reinforcement learning. Additionally, graduates can pursue careers as Information Security Analysts, Network Architects, Database Administrators, and Systems Administrators, reflecting the comprehensive training provided. REVA University’s BCA – AI&ML program thus combines technical rigor with career-oriented learning, enabling students to make significant contributions to the technology landscape.

Key features of the Curriculum

• Flexible Duration and Structure: The curriculum offers a flexible duration of three to four years, divided into 6 or 8 semesters, with multiple entry and exit points. This structure accommodates a broad range of student needs and learning paces, providing certificates and diplomas at various stages.
• Comprehensive Credit Distribution: The curriculum encompasses a total of 125 credits for the 3-year program and 165 credits for the 4-year (Honours and Honours with Research) programs. It includes a balanced mix of Humanities & Social Science Courses, Management Courses, Program Core and Elective Courses, Open Electives, and a significant emphasis on hands-on learning through Projects, Seminars, and Internships.
• Innovative Course Structure: The curriculum envisages connect of core subjects with NEP and SEP and its encompassing elements such as Holistic and Integrated Education, 21st Century Skills, Flexibility and Choice, Environmental Awareness, Value Based Education, Emphasis on Innovation, Understanding Human Behaviour, Empathy and Social Awareness. The fundamentals will provide the requisite robust grounding in management/business, the liberal arts subjects would help in furthering that grounding and also enable pluggability into international higher education systems (from exchange and dual degree perspectives) and the elements of sustainability, technology and behavioural sciences will ensure holistic development in synch with NEP and SEP.
• Specializations and Practical Exposure: Students will have the opportunity to specialize in emerging areas of AI and Machine Learning Technologies through Core and Electives and gain practical experience through structured internships and project work. This practical exposure is designed to enhance employability and entrepreneurial capabilities.
• Research Orientation for Honours Students: The BCA (Honours with Research) in 4th Year offers a unique pathway for students interested in academic and research careers. With a focus on advanced data analysis, research methodology, and a dissertation, this track prepares students for challenges in academia and industry research roles. It will also give students an opportunity to pave their path to higher education in management and technical fields.