JNTUA B.TECH R 20 2-3 Syllabus For Artificial intelligence PDF 2022
February 9, 2022 2022-02-09 1:00JNTUA B.TECH R 20 2-3 Syllabus For Artificial intelligence PDF 2022
JNTUA B.TECH R 20 2-3 Syllabus For Artificial intelligence PDF 2022
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You will be able to find information about Artificial intelligence along with its Course Objectives and Course outcomes and also a list of textbook and reference books in this blog.You will get to learn a lot of new stuff and resolve a lot of questions you may have regarding Artificial intelligence after reading this blog. Artificial intelligence has 5 units altogether and you will be able to find notes for every unit on the CynoHub app. Artificial intelligence can be learnt easily as long as you have a well planned study schedule and practice all the previous question papers, which are also available on the CynoHub app.
All of the Topic and subtopics related to Artificial intelligence are mentioned below in detail. If you are having a hard time understanding Artificial intelligence or any other Engineering Subject of any semester or year then please watch the video lectures on the official CynoHub app as it has detailed explanations of each and every topic making your engineering experience easy and fun.
Artificial intelligence Unit One
Introduction
Introduction: What is AI, Foundations of AI, History of AI, The State of Art.Intelligent Agents: Agents and Environments, Good Behaviour: The Concept of Rationality, The Nature of Environments, The Structure of Agents.
Artificial intelligence Unit Two
Solving Problems by searching
Problem Solving Agents, Example problems, Searching for Solutions, Uninformed Search Strategies, Informed search strategies, Heuristic Functions, Beyond Classical Search: Local Search Algorithms and Optimization Problems, Local Search in Continues Spaces, Searching with Nondeterministic Actions, Searching with partial observations, online search agents and unknown environments.
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Artificial intelligence Unit Three
Reinforcement Learning & Natural Language Processing
Reinforcement Learning: Introduction, Passive Reinforcement Learning, Active Reinforcement Learning, Generalization in Reinforcement Learning, Policy Search, applications of RLNatural Language Processing: Language Models, Text Classification, Information Retrieval, Information Extraction.
Artificial intelligence Unit Four
Natural Language for Communication
Natural Language for Communication: Phrase structure grammars, Syntactic Analysis,Augmented Grammars and semantic Interpretation, Machine Translation, Speech RecognitionPerception: Image Formation, Early Image Processing Operations, Object Recognition by appearance, Reconstructing the 3D World, Object Recognition from Structural information, Using Vision.
Artificial intelligence Unit Five
Robotics
Robotics: Introduction, Robot Hardware, Robotic Perception, Planning to move, Planning uncertain movements, Moving, Robotic software architectures, application domainsPhilosophical foundations: Weak AI, Strong AI, Ethics and Risks of AI, Agent Components, Agent Architectures, Are we going in the right direction, What if AI does succeed.
Artificial intelligence Course Objectives
•To introduce Artificial Intelligence•To Teach about the machine learning environment•To Present the searching Technique for Problem Solving•To Introduce Natural Language Processing and Robotics
Artificial intelligence Course Outcomes
After completion of the course, students will be able to•Apply searching techniques for solving a problem •Design Intelligent Agents •Develop Natural Language Interface for Machines •Design mini robots •Summarize past, present and future of Artificial Intelligence
Artificial intelligence Text Books
1.Stuart J.Russell, Peter Norvig, “Artificial Intelligence A Modern Approach”, 3rdEdition, Pearson Education, 2019.
Artificial intelligence Reference Books
1.Nilsson, Nils J., and Nils Johan Nilsson. Artificial intelligence: a new synthesis. Morgan Kaufmann, 1998.
2.Johnson, Benny G., Fred Phillips, and Linda G. Chase. “An intelligent tutoring system for the accounting cycle: Enhancing textbook homework with artificial intelligence.” Journal of Accounting Education 27.1 (2009): 30-39.
Scoring Marks in Artificial intelligence
Scoring a really good grade in Artificial intelligence is a difficult task indeed and CynoHub is here to help!. Please watch the video below and find out how to get 1st rank in your B.tech examinations . This video will also inform students on how to score high grades in Artificial intelligence. There are a lot of reasons for getting a bad score in your Artificial intelligence exam and this video will help you rectify your mistakes and help you improve your grades.
Information about JNTUA B.Tech R 20 Artificial intelligence was provided in detail in this article. To know more about the syllabus of other Engineering Subjects of JNTUH check out the official CynoHub application. Click below to download the CynoHub application.
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