Here Keralanotes.com will provide you KTU S7 CSE Artificial Intelligence - (CST401) Study materials. As technologies like ChatGPT advances the relevance of AI is growing. The purpose of the artificial intelligence course CST401 is to educate students on the basic ideas behind intelligent systems. This includes concepts related to knowledge representation techniques, logic, and inference procedures, as well as attributes of intelligent systems. The course aids the student in comprehending the design of self-learning systems as well as some of their usual applications in the growing scenario where machine learning advancements are revolutionizing the corporate world.
KTU S7 AI Notes 2019 Scheme of KTU Fourth Year Engineering 2019 Scheme. Notes are Easy to Understand and help to get a good score on KTU Exam. PDF Download of KTU Fourth Year Artificial Intelligence 2019 Scheme Notes (CST401).
| Board | KTU |
| Scheme | 2019 New Scheme |
| Year | Fourth Year |
| Semester | S7 |
| Subject | CST401 | Artificial Intelligence |
| Credit | 4 |
| Category | KTU S7 Computer Science & Engineering |
KTU S7 Artificial Intelligence | CST401 | Notes (2019 Scheme)
Module 1
Module 1 - Syllabus
Introduction: Introduction – What is Artificial Intelligence(AI)? The Foundations of AI, History of AI, Applications of AI.
Intelligent Agents – Agents and Environments, Good behavior: The concept of rationality, nature of Environments, Structure of Agents.
Module 1 - Notes
Module 1 Artificial Intelligence | CST 401 PPT Notes
Module 1 Artificial Intelligence | CST 401 PDF Notes
Module 2
Module 2 - Syllabus
Problem Solving: Solving Problems by searching-Problem solving Agents, Example problems, Searching for solutions, Uninformed search strategies, Informed search strategies, Heuristic functions.
Module 2 - Notes
Module 2 Artificial Intelligence | CST 401 PPT Notes
Module 2 Artificial Intelligence | CST 401 PDF Notes
Module 3
Module 3 - Syllabus
Search in Complex environments: Adversarial search - Games, Optimal decisions in games, The Minimax algorithm, Alpha-Beta pruning.
Constraint Satisfaction Problems – Defining CSP, Constraint Propagation- inference in CSPs, Backtracking search for CSPs, Structure of CSP problems.
Module 3 - Notes
Module 3 Artificial Intelligence | CST 401 PPT Notes
Module 3 Artificial Intelligence | CST 401 PDF Notes
Module 4
Module 4 - Syllabus
Knowledge Representation and Reasoning: Logical Agents – Knowledge based agents, Logic, Propositional Logic, Propositional Theorem proving, Agents based on Propositional Logic.
First Order Predicate Logic – Syntax and Semantics of First Order Logic, Using First Order Logic, Knowledge representation in First Order Logic. Inference in First Order Logic – Propositional Vs First Order inference, Unification and Lifting, Forward chaining, Backward chaining, Resolution.
Module 4 - Notes
Module 4 Artificial Intelligence | CST 401 PPT Notes
Module 4 Artificial Intelligence | CST 401 PDF Notes
Module 5
Module 5 - Syllabus
Machine Learning: Learning from Examples – Forms of Learning, Supervised Learning, Learning Decision Trees, Evaluating and choosing the best hypothesis, Regression and classification with Linear models.
Module 5 - Notes
Module 5 Artificial Intelligence | CST 401 PPT Notes
Module 5 Artificial Intelligence | CST 401 PDF Notes
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