Fundamentals of Artificial Intelligence
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Follow on Instagram for UpdatesFundamentals of Artificial Intelligence Syllabus — Unit-wise Content
The official GTU curriculum for Fundamentals of Artificial Intelligence (subject code ME01062041) as prescribed for IOT · Semester 1 divides the course into 5 units, covering 29 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 (ME01062041)Unit 1 UNIT- I
- Introduction to Artificial Intelligence(AI): Introduction and definition of Artificial Intelligence
- Intelligent Agents: Agents and Environments
- Nature of Environment
- Structure of Agent
- types of Agent
Unit 2 UNIT-II
- Problem Solving by Intelligent Search: Searching for solutions
- uninformed search strategies – Breadth-first search
- depth- first search
- Search with partial information (Heuristic search) Hill climbing
- AO* Program Name: Master of Engineering Level: PG Branch: Internet of Things Course / Subject Code : ME01062041 Course / Subject Name: Fundamentals of Artificial Intelligence
Unit 3 UNIT-III
- Soft Computing: Soft Computing: Introduction of soft computing
- soft computing Vs. hard computing
- various types of soft computing techniques
- Some applications of Soft computing techniques
- Introduction to Fuzzy Set: Fuzzy set theory
- Fuzzy set Vs crisp set, Crisp relation & fuzzy relations
- membership functions
- Fuzzy Logic: Fuzzy Logic basics
- Fuzzy Rules and Fuzzy Reasoning
- Fuzzy inference systems: Genetic algorithm: operators and constraints in genetic algorithm
Unit 4 UNIT-IV
- Artificial Neural Network: Introduction –Fundamental concept - Basic Models of Artificial Neural Networks –Important Terminologies of ANNs - McCulloch-Pitts Neuron
- Neural Network Architecture: Perceptron
- Single layer Feedforward ANN, Multilayer Feed Forward ANN, Supervised Learning: Delta learning rule
- Un- Supervised Learning algorithm: Self Organizing Maps
Unit 5 UNIT-V
- AI for IOT: Predictive Maintenance in IoT, Data-driven Approaches for Smart Homes and Cities
- Ethical AI for IoT Security
- Resource-constrained AI: Power and Performance
- AI Algorithms for Edge Computing Security Challenges in Edge Computing for IoT, Healthcare (AI-driven Healthcare IoT Solutions and data analytics
- ), and Industry 4.0
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