Introduction to Artificial Intelligence
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Follow on Instagram for UpdatesIntroduction to Artificial Intelligence Syllabus — Unit-wise Content
The official GTU curriculum for Introduction to Artificial Intelligence (subject code DI05024071) as prescribed for AI & DS · Semester 5 divides the course into 5 units, covering 33 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (DI05024071)Unit 1 Introduction to Artificial Intelligence
- Definition and concept of AI, History and evolution of AI, Types of AI, AI vs Machine Learning vs Deep Learning
- Intelligent systems
- AI applications in industries
- transportation and smart systems
- Advantages and limitations of AI
Unit 2 Intelligent Agents and Problem-Solving Intelligent agents and
- Characteristics of intelligent agents
- Problem-solving methods
- State space representation
- Searching techniques: Breadth First Search
- Depth First Search
- Heuristic Search
- Introduction to Expert Systems and Robotics
Unit 3 Machine Learning and Deep Learning Fundamentals
- Introduction to Machine Learning
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Pattern recognition
- Neural networks basics
- Deep Learning concepts
- AI datasets and training
- Applications of Machine Learning in industries
Unit 4 Generative AI and Prompt Engineering
- Introduction to Generative AI, Large Language Models (LLMs)
- AI chatbots and assistants
- Image generation AI tools
- AI productivity tools
- Basics of Prompt Engineering
- Types of prompts
- Effective prompt writing techniques
- AI applications in engineering education and industry
Unit 5 AI Ethics, Privacy and Future Trends
- AI ethics and responsible AI, Bias and fairness in AI, Data privacy and security
- AI regulations and challenges
- AI and employment
- social impact of AI, Explainable AI, Future trends in AI, Human-AI collaboration
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