AI Techniques
Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.
English Book & Chapters
English Book Coming Soon
We are working hard to add this material. Stay tuned for updates!
Follow on Instagram for UpdatesGTU Previous Year Papers
AI Techniques Syllabus — Unit-wise Content
The official GTU curriculum for AI Techniques (subject code 3710721) as prescribed for EE · Semester 1 divides the course into 3 units, covering 24 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 (3710721)Unit 1 Introduction
- The AI Problems
- The Underlying Assumption
- What is An AI Techniques? Difference between soft computing techniques and hard computing systems Expert systems brief history of ANN, Fuzzy and GA
Unit 2 Artificial Neural Networks
- Transient system model Introduction
- History of neural network research
- Basic concepts of Neural Networks
- Human brain
- Model of Artificial Neuron
- Neural Network architectures
- Single layer feed forward Network
- Multi layer feed forward network
- recurrent networks
- Feedback networks and Radial Basis Function Networks Characteristics of NN, Learning Methods
- LMS and Back Propagation Algorithm
- training Examples of models Advances in Neural networks
Unit 3 Fuzzy Logic
- Comparison between Fuzzy and crisp logic
- Fuzzy sets
- Membership function
- Basic fuzzy set operations
- properties of Fuzzy set, fuzzy relations
- Fuzzy interference system
- Fuzzy rule based system
- Defuzzification methods
- Fuzzy Neural Networks
Study on Android App:
