ASSEB Class 11 Artificial Intelligence Syllabus 2027 [HS 1st Year Artificial Intelligence Syllabus]

Artificial Intelligence (AI) is one of the fastest-growing technologies in the world. To prepare students for future careers, the Assam State School Education Board (ASSEB) has introduced Artificial Intelligence (AI Assistant) as a vocational skill subject for Class XI.

This syllabus helps students learn AI concepts from the basics to practical implementation using Python, Machine Learning, Data Analysis, AI Ethics, and real-world AI applications. The course follows the NSQF Level 4 framework and includes theory, practicals, projects, and case studies.

Course Overview

• Board: Assam State School Education Board (ASSEB)

• Class: XI

• Subject: Artificial Intelligence

• Job Role: AI Assistant

• Course Level: NSQF Level 4

• Academic Session: 2025–2026 Onwards

• Total Marks: 100

• Theory: 50 Marks

• Practical: 50 Marks

Objectives of the Course

The main objective of this course is to provide students with a strong foundation in Artificial Intelligence.

Students will learn:

• Introduction to Artificial Intelligence

• History and evolution of AI

• AI applications in different industries

• AI paradigms

• Programming using Python

• Mathematics required for AI

• Data Collection and Data Analysis

• Machine Learning

• Data Visualization

• AI Ethics

• Real-world AI projects and case studies

By the end of the course, students will be able to build simple AI models, analyze data, understand AI ethics, and solve real-life problems using Artificial Intelligence.

Learning Outcomes

After completing this syllabus, students will be able to:

• Understand the basic concepts of Artificial Intelligence.

• Explain AI applications in different industries.

• Develop Python programming skills.

• Apply mathematical concepts in AI.

• Work with datasets and perform data analysis.

• Build simple Machine Learning models.

• Create data visualizations.

• Understand ethical issues in AI.

• Develop practical AI projects using Python.

Marks Distribution

Part A – Employability Skills (10 Marks)

Unit	Marks
ICT Skills	4
Entrepreneurial Skills	4
Green Skills	2
Total	10

Part B – Subject Specific Skills (40 Marks)

Unit	Marks
Introduction to Artificial Intelligence	4
AI Paradigms	5
Programming for AI	5
Mathematics for AI	5
Data Literacy (Collection to Analysis)	6
Machine Learning Algorithms	6
Storytelling with Data	5
AI Ethics and Values	4
Total	40

Part C – Practical Work (50 Marks)

Practical Activity	Marks
Case Study Interpretation	10
Basic AI Project in Python	10
Practical File	5
AI Programming Practical	15
Internal Assessment	5
Viva Voce	5
Total	50

Complete Unit-wise Syllabus

Unit 1: Introduction to Artificial Intelligence

Students will study:

• What is Artificial Intelligence?

• History of AI

• Applications of AI

• Career opportunities in AI

Practical

• Research and present a real-life AI application such as Chatbots or Facial Recognition.

Unit 2: AI Paradigms

Topics include:

• Evolution of AI

• Symbolic AI

• Neuro-Symbolic AI

• Machine Learning

Practical

• Compare rule-based systems with learning-based systems.

Unit 3: Mathematics for AI

Students will learn:

• Linear Algebra

• Statistics

• Probability

• Calculus

Practical

• Solve AI-related mathematical problems.

Unit 4: Programming for AI

Topics covered:

• Python Programming

• Jupyter Notebook

• Google Colab

• Kaggle

• Variables

• Loops

• Functions

• File Handling

• Python Libraries:

• Random

• Math

• NumPy

• Pandas

• Matplotlib

Practical

• Write Python programs using Jupyter Notebook.

• Perform statistical analysis using Python libraries.

Unit 5: Machine Learning Paradigms

Students will study:

• Introduction to Machine Learning

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Machine Learning Workflow

Practical

• Run Machine Learning programs using Scikit-Learn.

Unit 6: Data Collection and Exploration

Topics include:

• Types of Data

• Data Formats

• Data Collection

• Data Cleaning

• Data Wrangling

• Data Exploration

Practical

• Clean datasets

• Perform Exploratory Data Analysis

• Create graphs using Matplotlib.

Unit 7: Supervised Learning Algorithms

Topics include:

• Linear Regression

• Support Vector Machine (SVM)

• K-Nearest Neighbors (KNN)

• Cross Validation

• Overfitting

• Regularization

• Performance Metrics

Practical

• Build Linear Regression models.

• Perform KNN Classification.

Unit 8: Unsupervised Learning Algorithms

Topics include:

• K-Means Clustering

• Principal Component Analysis (PCA)

Practical

• Perform K-Means Clustering.

• Apply Principal Component Analysis on datasets.

Unit 9: Storytelling with Data

Students will learn:

• Data Storytelling

• Understanding Audience

• Creating Data Narratives

• Visualization Principles

Practical

• Create dashboards using Python for data visualization.

Unit 10: AI Ethics

Topics include:

• Introduction to AI Ethics

• Ethical Principles

• AI Regulations

• AI Governance

Practical

• Analyze AI systems and discuss ethical considerations.

Unit 11: Case Studies & Project

Case Studies

Students will explore AI applications in:

• Computer Vision

• Natural Language Processing (NLP)

• Time Series Analysis

• Future AI Trends

Final Project

Develop a complete AI project in Python based on the concepts learned throughout the course.

Why Students Should Choose Artificial Intelligence?

Artificial Intelligence is becoming an essential skill for future careers. This course introduces students to modern AI technologies while building practical programming and analytical skills. Students gain experience in Python, Machine Learning, Data Science, and AI Ethics, making them better prepared for higher education and future employment in the technology sector.

Final Words

The ASSEB Class 11 Artificial Intelligence Syllabus provides a perfect blend of theory and practical learning. From Python programming to Machine Learning, Data Analysis, AI Ethics, and real-world projects, the syllabus equips students with the knowledge and skills required to begin their journey in Artificial Intelligence.