Course Objective:
To develop understanding, appreciation, and readiness for Artificial Intelligence (AI) and its real-life applications through interactive and hands-on learning.

Core Focus Areas:
Learners are introduced to the three major AI domains — Data Science, Computer Vision, and Natural Language Processing (NLP) — along with basic Python programming.

Learning Outcomes:
Students learn to identify AI applications, understand human–machine interactions, appreciate AI ethics, explore job opportunities, and connect AI with Sustainable Development Goals (SDGs).

Assessment Scheme:
Total marks: 100 (Theory 50 + Practical 50). The practical part includes project work, viva, and AI programming exercises.

Course Structure:

Part A: Employability Skills (Communication, ICT, Entrepreneurial, Green Skills).

Part B: Subject-Specific Skills (AI Introduction, AI Project Cycle, Advanced Python, Data Science, Computer Vision, NLP, Evaluation).

Part C: Practicals.

Part D: Project/Field Visit/Portfolio.

Key AI Units:

Introduction to AI – Basics, applications, ethics.

AI Project Cycle – Problem scoping, data acquisition, modelling, evaluation.

Data Science – Using NumPy, Pandas, Matplotlib.

Computer Vision – Image processing, OpenCV basics.

NLP – Text processing, chatbots, bag-of-words model.

Evaluation – Accuracy, precision, recall, F1-score.

Practical Component:
Minimum 15 Python programs covering list operations, data visualization, CSV handling, image reading, and statistical analysis.

Project Work / Portfolio:
Students must complete one project related to AI and SDGs (e.g., Student Marks Prediction Model, Fire Detection using CNN) or participate in AI exhibitions and hackathons.

Course Objective:
To develop understanding, appreciation, and readiness for Artificial Intelligence (AI) and its real-life applications through interactive and hands-on learning.

Core Focus Areas:
Learners are introduced to the three major AI domains — Data Science, Computer Vision, and Natural Language Processing (NLP) — along with basic Python programming.

Learning Outcomes:
Students learn to identify AI applications, understand human–machine interactions, appreciate AI ethics, explore job opportunities, and connect AI with Sustainable Development Goals (SDGs).

Assessment Scheme:
Total marks: 100 (Theory 50 + Practical 50). The practical part includes project work, viva, and AI programming exercises.

Course Structure:

Part A: Employability Skills (Communication, ICT, Entrepreneurial, Green Skills).

Part B: Subject-Specific Skills (AI Introduction, AI Project Cycle, Advanced Python, Data Science, Computer Vision, NLP, Evaluation).

Part C: Practicals.

Part D: Project/Field Visit/Portfolio.

Key AI Units:

Introduction to AI – Basics, applications, ethics.

AI Project Cycle – Problem scoping, data acquisition, modelling, evaluation.

Data Science – Using NumPy, Pandas, Matplotlib.

Computer Vision – Image processing, OpenCV basics.

NLP – Text processing, chatbots, bag-of-words model.

Evaluation – Accuracy, precision, recall, F1-score.

Practical Component:
Minimum 15 Python programs covering list operations, data visualization, CSV handling, image reading, and statistical analysis.

Project Work / Portfolio:
Students must complete one project related to AI and SDGs (e.g., Student Marks Prediction Model, Fire Detection using CNN) or participate in AI exhibitions and hackathons.

Foundations of Computer Systems

Basic computer organization, components, types of software, operating systems, Boolean logic, number systems, and encoding schemes.

Computational Thinking & Problem Solving

Algorithm design, flowcharts, pseudocode, and step-wise problem decomposition for programming logic.

Python Programming – I (Class XI)

Syntax, tokens, data types, operators, expressions, conditional and iterative statements, strings, lists, tuples, dictionaries, and Python modules.

Programming – II (Class XII)

User-defined functions, scope and parameters, exception handling, file handling (text, binary, CSV), and stack data structure.

Computer Networks

Evolution of networking, data communication concepts, transmission media, network devices, topologies, protocols, and web services (HTTP, HTML, XML).

Database Management Systems (DBMS)

Database concepts, relational data model, SQL (DDL, DML, joins, constraints), and Python-SQL connectivity for data-driven applications.

Society, Law & Ethics

Digital footprints, net etiquette, IPR, cybercrime, cyber safety, e-waste management, and social issues (gender and disability inclusion).

Practical Component (Class XI & XII)

Lab tests, report files, viva-voce, and programming projects emphasizing logical accuracy, documentation, and code quality.

Python-SQL Project Work

Real-world application projects combining file handling and database connectivity; promotes collaboration and innovation.

Foundations of Computer Systems

Basic computer organization, components, types of software, operating systems, Boolean logic, number systems, and encoding schemes.

Computational Thinking & Problem Solving

Algorithm design, flowcharts, pseudocode, and step-wise problem decomposition for programming logic.

Python Programming – I (Class XI)

Syntax, tokens, data types, operators, expressions, conditional and iterative statements, strings, lists, tuples, dictionaries, and Python modules.

Programming – II (Class XII)

User-defined functions, scope and parameters, exception handling, file handling (text, binary, CSV), and stack data structure.

Computer Networks

Evolution of networking, data communication concepts, transmission media, network devices, topologies, protocols, and web services (HTTP, HTML, XML).

Database Management Systems (DBMS)

Database concepts, relational data model, SQL (DDL, DML, joins, constraints), and Python-SQL connectivity for data-driven applications.

Society, Law & Ethics

Digital footprints, net etiquette, IPR, cybercrime, cyber safety, e-waste management, and social issues (gender and disability inclusion).

Practical Component (Class XI & XII)

Lab tests, report files, viva-voce, and programming projects emphasizing logical accuracy, documentation, and code quality.

Python-SQL Project Work

Real-world application projects combining file handling and database connectivity; promotes collaboration and innovation.

Introduction to Computer Systems

Evolution of computing devices, components of a computer system, input/output devices, memory types, data security, and types of software (system and application).

Python Programming Fundamentals

Basics of Python: syntax, operators, data types, expressions, control statements, loops, lists, and dictionaries.

Introduction to NumPy and creating arrays from lists.

Database Concepts & SQL (Class XI)

Introduction to databases and RDBMS, data models, and SQL operations: CREATE, SELECT, INSERT, UPDATE, DELETE, and filtering with WHERE, BETWEEN, and logical operators.

Emerging Technologies

Overview of AI, Machine Learning, NLP, AR/VR, Robotics, Big Data, IoT, Cloud and Grid Computing, and Blockchain technology.

Data Handling with Pandas (Class XII)

Working with Pandas Series and DataFrames: creation, indexing, slicing, and performing operations using Python.

Importing/exporting data between CSV files and DataFrames.

Data Visualization

Using Matplotlib for creating line, bar, and histogram plots; customizing charts with labels, titles, and legends for data interpretation.

Advanced SQL Operations

Use of mathematical, text, and date functions; aggregate functions; Group By, Having, and Join operations for relational data management.

Computer Networks & Internet Concepts

Basics of PAN, LAN, MAN, WAN; network devices and topologies; internet concepts like URL, WWW, web pages, and browser configuration.

Societal and Ethical Impacts of IT

Cyber safety, digital footprints, net etiquettes, data protection, intellectual property rights, plagiarism, e-waste management, and awareness about tech-related health issues.

Practical and Project Work

Hands-on Python and SQL exercises, Pandas and Matplotlib applications, and a project integrating Class XI–XII concepts.

Introduction to Computer Systems

Evolution of computing devices, components of a computer system, input/output devices, memory types, data security, and types of software (system and application).

Python Programming Fundamentals

Basics of Python: syntax, operators, data types, expressions, control statements, loops, lists, and dictionaries.

Introduction to NumPy and creating arrays from lists.

Database Concepts & SQL (Class XI)

Introduction to databases and RDBMS, data models, and SQL operations: CREATE, SELECT, INSERT, UPDATE, DELETE, and filtering with WHERE, BETWEEN, and logical operators.

Emerging Technologies

Overview of AI, Machine Learning, NLP, AR/VR, Robotics, Big Data, IoT, Cloud and Grid Computing, and Blockchain technology.

Data Handling with Pandas (Class XII)

Working with Pandas Series and DataFrames: creation, indexing, slicing, and performing operations using Python.

Importing/exporting data between CSV files and DataFrames.

Data Visualization

Using Matplotlib for creating line, bar, and histogram plots; customizing charts with labels, titles, and legends for data interpretation.

Advanced SQL Operations

Use of mathematical, text, and date functions; aggregate functions; Group By, Having, and Join operations for relational data management.

Computer Networks & Internet Concepts

Basics of PAN, LAN, MAN, WAN; network devices and topologies; internet concepts like URL, WWW, web pages, and browser configuration.

Societal and Ethical Impacts of IT

Cyber safety, digital footprints, net etiquettes, data protection, intellectual property rights, plagiarism, e-waste management, and awareness about tech-related health issues.

Practical and Project Work

Hands-on Python and SQL exercises, Pandas and Matplotlib applications, and a project integrating Class XI–XII concepts.

Course Overview:

This course covers the fundamental concepts of computer system organization, programming, efficient mechanism

for storing and retrieving data on main memory, data management and visualization techniques, computer networks

along with HTML page designing, the value of technology in societies, e-commerce, database management system,

artificial intelligence, and data warehouse and data mining technique for the students from all academic backgrounds.

Course Objective:

This course enables students to-

 develop an understanding of how computer system works; the components of computer systems and how

they interrelate, including software, data, hardware, communications and users.

 analyze a computing problem and to apply principles of computing to identify solutions.

 use of efficient data storing and retrieval technique along with basic programming skill.

 gather the fundamental knowledge on computer networks and web page designing.

 gain proficiency in data management, visualization, analysis, and presentation using a widely-used open

source spreadsheet software application such as Open Office, Libre Office, or Google Spreadsheets.

 appreciate the ethical implications relating to the use of computing technology and information and identify

the impact of technology on personal life and society.

 develop the knowledge, skills, and competencies needed to leverage the opportunities presented by the

digital economy and to navigate the challenges and risks associated with online business operations.

 understand the basics of artificial intelligence and its subfields.

 develop an understanding of database management systems, with an emphasis on how to organize, maintain

and retrieve - efficiently, and effectively.

 extract knowledge from data repository for data analysis, frequent pattern, classification and prediction.

Course Overview:

This course covers the fundamental concepts of computer system organization, programming, efficient mechanism

for storing and retrieving data on main memory, data management and visualization techniques, computer networks

along with HTML page designing, the value of technology in societies, e-commerce, database management system,

artificial intelligence, and data warehouse and data mining technique for the students from all academic backgrounds.

Course Objective:

This course enables students to-

 develop an understanding of how computer system works; the components of computer systems and how

they interrelate, including software, data, hardware, communications and users.

 analyze a computing problem and to apply principles of computing to identify solutions.

 use of efficient data storing and retrieval technique along with basic programming skill.

 gather the fundamental knowledge on computer networks and web page designing.

 gain proficiency in data management, visualization, analysis, and presentation using a widely-used open

source spreadsheet software application such as Open Office, Libre Office, or Google Spreadsheets.

 appreciate the ethical implications relating to the use of computing technology and information and identify

the impact of technology on personal life and society.

 develop the knowledge, skills, and competencies needed to leverage the opportunities presented by the

digital economy and to navigate the challenges and risks associated with online business operations.

 understand the basics of artificial intelligence and its subfields.

 develop an understanding of database management systems, with an emphasis on how to organize, maintain

and retrieve - efficiently, and effectively.

 extract knowledge from data repository for data analysis, frequent pattern, classification and prediction.

Course Overview:

This course covers the fundamental concepts of computer system organization, programming fundamental along

with its theoretical analysis, data structure, computer networks, the value of technology in societies, e-commerce,

python programming, database management system, and artificial intelligence for the students from science

background only.

Course Objective:

This course enables students to-

 develop an understanding of how computer system works; the components of computer systems and how

they interrelate, including software, data, hardware, communications and users.

 analyse a computing problem and to apply principles of computing to identify solutions.

 use of efficient data storing and retrieval technique along with basic programming skill.

 gather the fundamental knowledge on computer networks and web page designing.

 appreciate the ethical implications relating to the use of computing technology and information and identify

the impact of technology on personal life and society.

 develop the knowledge, skills, and competencies needed to leverage the opportunities presented by the

digital economy and to navigate the challenges and risks associated with online business operations.

 understand the basics of artificial intelligence and its subfields.

 develop an understanding of database management systems, with an emphasis on how to organize,

maintain and retrieve - efficiently, and effectively.

Course Overview:

This course covers the fundamental concepts of computer system organization, programming fundamental along

with its theoretical analysis, data structure, computer networks, the value of technology in societies, e-commerce,

python programming, database management system, and artificial intelligence for the students from science

background only.

Course Objective:

This course enables students to-

 develop an understanding of how computer system works; the components of computer systems and how

they interrelate, including software, data, hardware, communications and users.

 analyse a computing problem and to apply principles of computing to identify solutions.

 use of efficient data storing and retrieval technique along with basic programming skill.

 gather the fundamental knowledge on computer networks and web page designing.

 appreciate the ethical implications relating to the use of computing technology and information and identify

the impact of technology on personal life and society.

 develop the knowledge, skills, and competencies needed to leverage the opportunities presented by the

digital economy and to navigate the challenges and risks associated with online business operations.

 understand the basics of artificial intelligence and its subfields.

 develop an understanding of database management systems, with an emphasis on how to organize,

maintain and retrieve - efficiently, and effectively.