CBSE Class 10 Artificial Intelligence Syllabus 2025-26
CBSE Class 10 Artificial Intelligence Syllabus 2025-26: The Central Board of Secondary Education has published the latest syllabus for Class 10 Artificial Intelligence for the academic year 2025-26. Students and teachers can download the CBSE syllabus for Class 10 Artificial Intelligence in PDF for free.
The Central Board of Secondary Education (CBSE) has introduced the Class 10 Artificial Intelligence (AI) syllabus for the academic year 2025-26. This curriculum is designed to provide students with a foundational understanding of AI concepts, applications, and ethical considerations, equipping them with skills relevant to the evolving technological landscape.
Objectives of the Course:
The AI curriculum aims to:
- Foster an understanding of Artificial Intelligence and its real-world applications.
- Introduce students to the three domains of AI through interactive learning methods.
- Engage students in hands-on activities to construct meaningful insights about AI.
- Familiarize students with the AI Project Cycle.
- Develop basic programming skills using Python.
Course Structure:
The syllabus is divided into four parts:
- Part A: Employability Skills
- Part B: Subject-Specific Skills
- Part C: Practical Work
- Part D: Project Work/Field Visit/Student Portfolio
Part A: Employability Skills
This section covers essential skills to enhance students’ employability prospects:
- Communication Skills-II: Effective communication techniques.
- Self-Management Skills-II: Personal development and time management.
- Information and Communication Technology Skills-II: Proficiency in using digital tools.
- Entrepreneurial Skills-II: Basics of entrepreneurship and innovation.
- Green Skills-II: Awareness about sustainable practices.
Part B: Subject-Specific Skills
This section delves into core AI concepts:
- Introduction to Artificial Intelligence: Overview and significance of AI.
- AI Project Cycle: Stages involved in developing AI projects.
- Advance Python: In-depth programming concepts in Python.
- Data Science: Introduction to data handling and analysis.
- Computer Vision: Basics of enabling machines to interpret visual data.
- Natural Language Processing: Techniques for computers to understand human language.
- Evaluation: Assessing AI models and their performance.
Part C: Practical Work
Practical sessions include:
- Maintaining a practical file with at least 15 Python programs.
- Hands-on exercises related to Data Science, Computer Vision, and Natural Language Processing.
- Practical examinations and viva voce assessments.
Part D: Project Work/Field Visit/Student Portfolio
Students are required to undertake:
- Projects or field visits related to AI applications.
- Compilation of a portfolio showcasing their learning experiences.
- Presentation and viva voce based on their project work.
This comprehensive syllabus is structured to balance theoretical knowledge with practical application, ensuring students gain a robust understanding of Artificial Intelligence. For detailed information and updates, students and educators are advised to refer to official CBSE resources.