CBSE Class 10 Artificial Intelligence 2025 Syllabus

Part B which is subject specific skills has seven units: (i) Introduction to Artificial Intelligence (AI) (ii) AI Project Cycle (iii) Advance Python (iv) Data Science (v) Computer Vision (vi) Natural Language Processing (vii) Evaluation.

Part B: Subject Specific Skills

Unit Name Marks
1 Introduction to Artificial Intelligence (AI) 7
2 AI Project Cycle 9
3 Advance Python -
4 Data Science 4
5 Computer Vision 4
6 Natural Language Processing 8
7 Evaluation 8
  Total 40

Part C: Practical Work

  • Unit 3: Advance Python
  • Unit 4: Data Science
  • Unit 5: Computer Vision

Unit 1: Introduction to Artificial Intelligence (AI)

Foundational concepts of AI

  • Understand the concept of human intelligence and its various components such as reasoning, problem-solving, and creativity.

Basics of AI: Let’s Get Started

  • Understand the concept of Artificial Intelligence (AI) and its domains.
  • Explore the use of AI in real Life.
  • Learn about the ethical concerns involved in AI development, such as AI bias, data privacy and how they can be addressed.

Unit 2: AI Project Cycle

Introduction

  • Understand the stages involved in the AI project cycle, such as problem scoping, data collection, data exploration, modeling, evaluation.

Problem Scoping

  • Learn about the importance of project planning in AI development and how to define project goals and objectives.

Data Acquisition

  • Develop an understanding of the importance of data collection in AI and how to choose the right data sources.

Data Exploration

  • Know various data exploration techniques and its importance.

Modelling

  • Know about the different machine learning algorithms used to train AI models.

Evaluation

  • Know the importance of evaluation and various metrics available for evaluation.

Unit 3: Advance Python

(To be assessed through Practicals)

Recap

  • Understand to work with Jupyter Notebook, creating virtual environment, installing Python Packages.
  • Able to write basic Python programs using fundamental concepts such as variables, data types, operators, and control structures.
  • Able to use Python built-in functions and libraries.

Unit 4: Data Science

Introduction

  • Define the concept of Data Science and understand its applications in various fields.

Getting Started

  • Understand the basic concepts of data acquisition, visualization, and exploration.

Unit 5: Computer Vision

Introduction

  • Define the concept of Computer Vision and understand its applications in various fields.

Concepts of Computer Vision

  • Understand the basic concepts of image representation, feature extraction, object detection, and segmentation.

Unit 6: Natural Language Processing

Introduction

  • Understand the concept of Natural Language Processing (NLP) and its importance in the field of Artificial Intelligence (AI).

Chatbots

  • Explore the various applications of NLP in everyday life, such as chatbots, sentiment analysis, and automatic summarization

Language Differences

  • Gain an understanding of the challenges involved in understanding human language by machine.

Concepts of Natural Language Processing

  • Learn about the Text Normalization technique used in NLP and popular NLP model - Bag-of-Words

Unit 7: Evaluation

Introduction

  • Understand the role of evaluation in the development and implementation of AI systems.

Model Evaluation Terminology

  • Learn various Model Evaluation Terminologies

Confusion Matrix

  • Learn to make a confusion matrix for given Scenario

Evaluation Methods

  • Learn about the different types of evaluation techniques in AI, such as Accuracy, Precision, Recall and F1 Score, and their significance.