Thangal Kunju Musaliar Institute of Technology Kollam B.Tech Computer Science Engineering - Artificial Intelligence: Fees 2026, Course Duration, Dates, Eligibility

Ans. TKMIT offers three closely related CS programmes: CSE, CS (AI), and CS (AI & ML). B.Tech CSE is the traditional computer science programme covering broad software and hardware topics. B.Tech CS (AI) focuses specifically on artificial intelligence including Machine Learning, Deep Learning, NLP, Computer Vision, Robotics, and AI Ethics, making it ideal for students interested in AI research and applied AI development. B.Tech CS (AI & ML) has a stronger emphasis on machine learning methodologies and data science tools like TensorFlow and PyTorch. Students interested in robotics, AI ethics, and broader AI applications may prefer CS (AI), while those focused on data science and ML engineering may prefer CS (AI & ML). All three have the same fee structure and are admitted through KEAM.

Ans. The inclusion of AI Ethics in the B.Tech CS (AI) curriculum at TKMIT reflects the growing global emphasis on responsible AI development. As AI systems are increasingly deployed in healthcare, finance, law, and governance, understanding the ethical, legal, and societal implications of AI is becoming a critical skill for AI engineers. This differentiates the CS (AI) programme from purely technical AI courses and prepares graduates for roles in AI policy, AI governance, and responsible AI product development, in addition to traditional software and AI engineering roles. This is particularly relevant for students interested in working with global tech companies or pursuing research in AI safety.

Ans. The CS (AI) programme at TKMIT was launched in 2023, meaning the first batch will graduate around 2027. There is no programme-specific placement data yet. However, TKMIT's overall CS placement record is strong, with companies like Juspay, Oracle, Commvault, and others visiting the campus, with packages ranging from 4-5 LPA average to 21-33 LPA for top offers. AI and ML skills are among the most in-demand in the tech industry, and graduates with strong foundations in Python, deep learning, and NLP are well-positioned for roles at product companies, IT services firms, and startups. Students are advised to supplement their degree with internships, Kaggle competitions, and certifications.

Ans. The AI and Robotics Lab at TKMIT is a dedicated facility for exploring artificial intelligence, robotics, and automation technologies. Students in the CS (AI) programme can work on projects involving autonomous systems, robotic process automation, computer vision applications, and AI-powered IoT devices. The lab is equipped with the latest hardware and software to support hands-on learning and project-based education. Students can also participate in national-level robotics competitions, hackathons, and research projects through the lab. The combination of AI theory and robotics practice makes this programme particularly suitable for students interested in embedded AI and intelligent systems.

Ans. The B.Tech CS (AI) programme at TKMIT is AICTE-approved and affiliated to KTU, which are the standard requirements for recognition in India and most international universities. For higher studies abroad (MS/PhD), the programme's KTU affiliation and AICTE approval are generally accepted by foreign universities, though individual university requirements may vary. For government jobs in India (PSUs, UPSC, state PSCs), the eligibility is typically based on the B.Tech degree in Computer Science or related engineering disciplines, and CS (AI) graduates should qualify. Students planning for GATE should note that GATE CS paper covers core CS topics, which are well-covered in this curriculum.

Ans. The B.Tech CS (AI) programme at TKMIT has a sanctioned intake of 60 students per year. Based on the 2024-25 mandatory disclosure, actual admissions were 61 students for the CS (AI) batch, indicating near-full utilisation of seats. TKMIT has a dedicated faculty team for the CS department with qualified professors holding M.Tech and Ph.D. degrees. The relatively small batch size compared to larger institutions ensures better faculty-student interaction, more personalised attention in labs, and greater opportunities for project guidance. The college's advisory system assigns a senior advisor to approximately 20 students per batch, ensuring academic and personal support throughout the programme.