Artificial Intelligence 11
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Welcome!
Artificial Intelligence for CBSE Class 11 is a 100-mark subject covering topics such as AI introduction, Python programming, data literacy, machine learning algorithms, and AI ethics. The syllabus also includes a Capstone Project and Employability Skills. The assessment comprises a 50-mark theory exam and a 50-mark practical exam.
Prerequisites
Prerequisites for learning Artificial Intelligence in CBSE Class 11 include a basic understanding of computer fundamentals, logical reasoning skills, and familiarity with mathematics, particularly statistics. Prior knowledge of programming, especially Python, is also beneficial for effective learning.
Learning Objectives
Learning objectives for Artificial Intelligence for CBSE Class 11 students include understanding AI concepts, developing programming skills in Python, applying data analysis techniques, creating AI models, and enhancing problem-solving abilities while fostering critical thinking and collaboration through practical projects and case studies.
Course Overview
- Overview of Artificial Intelligence (AI)
- Importance and impact of AI in daily life
- Key concepts and terminologies in AI
- Career opportunities in AI and related fields
- Skills required for AI professionals
- Future trends and advancements in AI technology
- Introduction to Python programming language
- Basic syntax, data types, and control structures
- Functions, libraries, and modules in Python
- Hands-on exercises to build foundational programming skills
- Understanding the Capstone Project concept
- Steps to plan and execute a Capstone Project
- Identifying real-world problems to solve using AI
- Project presentation and evaluation criteria
- Importance of data in AI applications
- Methods of data collection and data sources
- Data cleaning, preprocessing, and exploration
- Basic statistical analysis and data visualization techniques
- Introduction to machine learning concepts
- Supervised vs. unsupervised learning
- Common machine learning algorithms (e.g., linear regression, decision trees, clustering)
- Practical implementation of algorithms using Python
- Intersection of linguistics and AI (Natural Language Processing)
- Key NLP concepts and applications
- Analyzing and processing textual data
- Hands-on projects involving text-based AI applications
- Understanding ethical considerations in AI
- Privacy, bias, and fairness in AI systems
- The role of AI in society and responsible AI development
- Discussion on current ethical dilemmas in AI
- Communication Skills
- Self-management Skills
- Information and Communication Technology Skills
- Entrepreneurial Skills
- Green Skills
IBM Skills Build Certification/any other industry certification 5 Marks
Capstone Project 12 Marks
Bootcamps/ Internship/other startups 7 Marks
Practical File 10 Marks
Written Exam 10 Marks
Viva Voce 6 Marks
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Placement assistance offered for a successful career.
Membership
Membership provided until the final examination.
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Personalized attention provided to each student.
Get Course Certificate
Certificate awarded upon completion of the course.
Monthly Tests
Regular monthly test series for progress evaluation.
Latest CBSE Syllabus
Training modules aligned with the latest CBSE syllabus.
Frequently Asked Questions
It includes topics like AI introduction, Python programming, data literacy, machine learning, and AI ethics.
Basic knowledge of Python is helpful but not mandatory.
You’ll work on a Capstone Project, applying AI concepts to real-world problems.
The assessment includes a 50-mark theory exam and a 50-mark practical exam.
You’ll learn Python programming, data handling, AI modeling, and ethical considerations.
AI skills open up opportunities in technology fields, enhancing future career prospects.
