In this article, you'll find the complete ASSEB HS 2nd Year Artificial Intelligence Syllabus 2027, including all units, important topics, learning outcomes, and practical work.
ASSEB Class 12 Artificial Intelligence Syllabus 2027 Overview
| Particular | Details |
|---|---|
| Board | Assam State School Education Board (ASSEB) |
| Class | Class 12 (HS 2nd Year) |
| Subject | Artificial Intelligence II |
| Session | 2027 |
| Level | Senior Secondary |
The Class 12 AI course builds upon the concepts learned in Class 11 and introduces advanced Artificial Intelligence techniques such as Neural Networks, Deep Learning, Generative AI, Multimodal AI, Explainable AI, Sustainable AI, and Capstone Projects.
Learning Outcomes
After completing this course, students will be able to:
- Design and implement advanced AI models.
- Understand Artificial Neural Networks and Deep Learning.
- Build AI applications using modern frameworks.
- Explore Generative AI and Multimodal AI.
- Understand Explainable AI (XAI).
- Develop AI solutions for real-world problems.
- Complete an end-to-end AI Capstone Project.
Complete ASSEB Class 12 Artificial Intelligence Syllabus 2027
Unit 1: Artificial Neural Networks (ANN)
Theory Topics
- Introduction to Artificial Neural Networks
- Perceptron
- Multilayer Perceptron
- Backpropagation
- Activation Functions
Practical
- Introduction to ANN using Scikit-learn
- Predict housing prices using a Neural Network.
Unit 2: Deep Neural Networks
Theory Topics
- Deep Learning Concepts
- Convolutional Neural Networks (CNN)
- Pooling
- Recurrent Neural Networks (RNN)
- Attention Mechanism
- Transformer Architecture
Practical
- Introduction to PyTorch
- Train a CNN using the MNIST handwritten digit dataset.
Unit 3: Generative AI
Theory Topics
- Introduction to Generative AI
- Autoencoders
- Generative Adversarial Networks (GANs)
- Large Language Models (LLMs)
- Applications of Generative AI
Practical
- Generate images using a pre-trained GAN model.
Unit 4: Multimodal AI
Theory Topics
- Introduction to Multimodal AI
- Combining Text, Images and Audio
- Multimodal AI Applications
Practical
- Build a multimodal sentiment analysis model using text and images.
Unit 5: Explainability in AI (XAI)
Theory Topics
- Explainable AI (XAI)
- Importance of Explainability
- Accuracy vs Interpretability
- SHAP
- LIME
Practical
- Explain Machine Learning predictions using SHAP or LIME.
Unit 6: Sustainable AI and SDGs
Theory Topics
- Introduction to Sustainable AI
- United Nations Sustainable Development Goals (SDGs)
- AI Applications for SDGs
- Ethical, Social and Environmental Challenges
Practical
- Prepare a presentation on an AI model aligned with the Sustainable Development Goals.
Unit 7: Case Study
Topics Covered
- Real-world Deep Neural Network Applications
- Computer Vision
- Natural Language Processing (NLP)
- Time Series Analysis
- Future Trends in Artificial Intelligence
- Successes and Failures of AI Projects.
Unit 8: Capstone Project
Students will complete a comprehensive AI project involving:
- Problem Identification
- Data Collection
- Model Development
- Result Analysis
- Presentation and Visualization
- End-to-End AI Solution Development.
Why Study Artificial Intelligence in Class 12?
The Artificial Intelligence syllabus prepares students for higher education and future careers in:
- Artificial Intelligence
- Machine Learning
- Data Science
- Robotics
- Computer Science
- Software Development
- Research and Innovation
The course also develops problem-solving, programming, analytical thinking, and project development skills.
Final Words
The ASSEB Class 12 Artificial Intelligence Syllabus 2027 offers students a strong foundation in advanced AI concepts through both theoretical learning and practical implementation. With topics like Neural Networks, Deep Learning, Generative AI, Explainable AI, Sustainable AI, and a Capstone Project, students gain the knowledge and skills required for future studies and careers in Artificial Intelligence.
