Bachelor of Computer Applications AI Program Overview
The Bachelor of Computer Applications AI provides a comprehensive academic foundation with industry-relevant curriculum, practical learning, and career-focused education designed for professional success.
The program builds expertise in AI, Machine Learning, and AI-driven Full Stack Development through IBM-led learning, hands-on projects, bootcamps, and internships, preparing students for careers in the AI-driven digital economy.
Students learn programming fundamentals, full stack architectures, AI algorithms, machine learning models, data handling, automation tools, and software development practices for building intelligent, scalable digital systems.
Admission At A Glance
Duration
3 Degree /4 Honors Years
Semesters
6 Semesters
Scholarship
Available
Program Fees
โน1,50,000 Per Year
Eligibility
Qualification
10+2 or equivalent
Subjects Required
Minimum Score
60% aggregate
Entrance Exams
Program Highlights
The Bachelor of Computer Applications AI offers industry exposure, modern infrastructure, expert faculty, internships, skill development, and holistic campus learning experiences.
Industry-Integrated AI Learning with IBM ICE
Curriculum aligned with real-world AI and emerging technology trends.
IBM-Led Experiential Learning
Bootcamps, hackathons, and hands-on projects guided by industry experts.
100% Internship, Placement and Entrepreneurship assistance
Maximize your career potential through guaranteed internships, targeted job placements, and expert startup support.
Specialization in AI/ML & AI-Driven Full Stack Development
Build intelligent systems and end-to-end applications.
Industry Collaborations
The Bachelor of Computer Applications AI program integrates active industry collaboration, offering internships, live projects, industry mentorship, real-world exposure, and skill-based learning to enhance employability and ensure alignment with current industry practices
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IBM Innovation Centre for Education
๐ก ๐ช๐ต๐ฎ๐ ๐๐๐๐ฑ๐ฒ๐ป๐๐ ๐ด๐ฎ๐ถ๐ป: Students benefit from IBM-led specialized subjects, industry-aligned hands-on learning, globally recognized IBM digital badges, immersive bootcamps and hackathons, along with valuable internships and real-world exposure that prepare them for dynamic, future-ready careers.
Major Specialization Tracks
The Bachelor of Computer Applications AI offers specialized career tracks in high-demand domains, helping students build expertise, innovation skills, and professional competence. Students may select a BCA Artificial Intelligence specialization to develop deep expertise. Elective subjects will be based on the chosen track of BCA Artificial Intelligence course.
AI driven Full stack development
Focuses on integrating full-stack web development with AI, machine learning, cloud deployment, and user-centric design for building intelligent digital applications.
Syllabus
The Bachelor of Computer Applications AI syllabus integrates core fundamentals, emerging technologies, interdisciplinary subjects, and practical training aligned with current industry trends.The BCA Artificial Intelligence syllabus is designed to build essential knowledge, practical skills, and leadership qualities for success in todayโs evolving professional world
The syllabus progresses from programming and web fundamentals to advanced full-stack development, applied machine learning, and the integration of AI in software projects.
Year-wise Syllabus
Year 1: Foundation Year
Program Outcomes
The Bachelor of Computer Applications AI helps students achieve strong technical knowledge, critical thinking, professional skills, research aptitude, and global career readiness.
- Design intelligent applications using AI and machine learning techniques.
- Develop full stack software for web and mobile platforms.
- Implement automation and AI-driven solutions in real-world projects
- Analyze data to optimize applications and business processes.
Career Opportunities
The Bachelor of Computer Applications AI prepares graduates for diverse career opportunities, top industry roles, entrepreneurship, higher education, and global employment prospects.
To apply for the Bachelor of Computer Applications AI programme at Pillai University, one of the top private universities in Mumbai, candidates must meet the following criteria:
BCA Artificial Intelligence Eligibility:
Candidates must have completed 10+2 or equivalent, securing a minimum of 60% aggregate (as per university norms).BCA Artificial Intelligence Entrance Exams:
A valid score in PULSE (Pillai University Level Scholastic Exam), CUET (Common University Entrance Test), SET (Symbiosis Entrance Test), MET (Manipal Entrance Test), Recognized state-level entrance examinations or other recognised national/state-level tests is required. These exams are used for merit-based selection into the programme.BCA Artificial Intelligence Application Process:
Applications are submitted online through the university portal. Shortlisted candidates may be called for counselling or personal interaction as per university guidelines.BCA Artificial Intelligence Duration & Semesters:
The programme runs for 3 Degree /4 Honors years, comprising 6 semesters.BCA Artificial Intelligence Fee:
Approximately โน1,50,000 per annum.BCA Artificial Intelligence Cutoff:
The cutoff for the Bachelor of Computer Applications AI programme will be announced soon. For more information, contact +91 881 882 8837.BCA Artificial Intelligence Scholarship:
Eligible students may apply for Scholarships, awarded as per merit and university policies.Required Documents:
- S.S.C. and H.S.C. marksheets & passing certificates
- Transfer/Leaving Certificate
- Caste Certificate (if applicable)
- Non-Creamy Layer Certificate (for DT/VJ, NT, OBC, SBC categories)
- Migration Certificate (if applicable)
- Domicile Certificate
- Aadhar Card copy
- Income Certificate (if applicable)
- Anti-Ragging Affidavit (signed and submitted online)
Highlights:
Pillai University, recognised among the best universities in Mumbai and a top university in Navi Mumbai, offers industry-aligned, career-oriented programmes with global exposure, experiential learning, and research-driven education.
