Artificial And Machine Learning Lab 

For students in the CBSE curriculum, AI and ML labs offer hands-on learning through dedicated school facilities and vendor-provided kits and platforms. CBSE provides an official syllabus for Artificial Intelligence as a skill subject, which is often implemented through such labs. 

Implementation of AI/ML labs in CBSE schools

• Atal Tinkering Labs (ATL): Many CBSE-affiliated schools that have established ATLs use this government-funded infrastructure to provide hands-on experience in AI and robotics. Some ATLs specifically incorporate AI modules.
• Third-party vendors: Companies like STEMpedia, STEMROBO, and RobotLAB partner with CBSE schools to set up dedicated AI and ML labs. These vendors offer comprehensive packages that include:
  • Curriculum aligned with CBSE syllabus
  • AI and robotics kits
  • Python-based coding software
  • Teacher training programs
  • Learning management systems
• PM SHRI Labs: The PM Schools for Rising India (PM SHRI) scheme also includes the establishment of multi-tech labs, with a focus on Artificial Intelligence and Machine Learning. 

CBSE AI and ML syllabus overview

CBSE offers AI as a skill subject (Code 417 for classes IX-X and Code 843 for classes XI-XII). The curriculum is structured to blend theoretical knowledge with practical, activity-based learning. 

Classes IX and X (Code 417)

• Introduction to AI: Covers basic concepts, applications in daily life, and the three main AI domains: Data Science, Natural Language Processing (NLP), and Computer Vision.
• AI Project Cycle: Teaches students the methodology for developing AI projects, from problem scoping to evaluation.
• Data Science: Includes concepts like data literacy and mathematics for AI (statistics and probability).
• Python: Students learn Python programming to work on AI concepts.
• Practical work and project: The course includes significant practical components and project-based assignments, focusing on real-world applications and sustainable development goals. 

Classes XI and XII (Code 843)

• Advanced AI concepts: Covers higher-level topics such as machine learning algorithms, deep learning, and advanced Python.
• Practical implementation: The syllabus includes practical labs focused on implementing various algorithms, including supervised, unsupervised, and reinforcement learning.
• Ethical AI: Discusses ethical considerations, biases, and data privacy related to AI. 

Benefits of AI/ML labs in schools

• Hands-on learning: Enables students to move beyond theoretical knowledge and apply AI concepts to real-world problems.
• Future skills: Equips students with 21st-century skills like critical thinking, problem-solving, and creativity, preparing them for future careers.
• Interdisciplinary approach: Connects AI concepts with other subjects like mathematics, science, and social studies.
• Increased engagement: Interactive tools and projects make learning more engaging for students of all ages.
• Ethical awareness: Promotes a responsible approach to technology by addressing issues like AI bias and ethical implications.