JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material/ Notes PDF Download

JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material
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JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material/ Notes PDF Download: Are you looking for JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material. Your search ends here! Our comprehensive materials cover everything you need to excel in AI studies, whether it’s understanding problem-solving methodologies, implementing fundamental AI algorithms, or conducting empirical evaluations of various algorithms for problem-solving. With our expertly crafted notes, you’ll grasp the essence of AI concepts and learn to apply them practically.

Additionally, we offer downloadable PDF versions of our materials for easy access anytime, anywhere. Get ready to ace your AI course with our extensive resources tailored specifically for JNTUK R20 B.Tech CSE students. Download our material now and take your AI knowledge to the next level!

JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material – Units

No. Of UnitsName of the Unit
Unit – 1Introduction to artificial intelligence
Unit – 2Problem-solving, Search Strategies
Unit – 3Logic concepts
Unit – 4Knowledge representation
Unit – 5Expert system and applications

Unit 1 Syllabus PDF Download | JNTUK R20 B.Tech Artificial Intelligence Material

Introduction to artificial intelligence: Introduction, history, intelligent systems, foundations of AI, applications, tic-tac-tie game playing, development of AI languages, current trends in AI.

JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material – PDF Download
To Download The JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Unit 1 Notes PDFDownload PDF

Unit 2 Syllabus PDF Download | JNTUK R20 B.Tech Artificial Intelligence Material

Problem-solving: state-space search and control strategies: Introduction, general problem solving, characteristics of problem

Search Strategies: exhaustive searches, heuristic search techniques, iterative-deepening A*, constraint satisfaction

JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material – PDF Download
To Download The JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Unit 2 Notes PDFDownload PDF

Unit 3 Syllabus PDF Download | JNTUK R20 B.Tech Artificial Intelligence Material

Logic concepts: Introduction, propositional calculus, proportional logic, natural deduction system, axiomatic system, semantic tableau system in proportional logic, predicate logic

JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material – PDF Download
To Download The JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Unit 3 Notes PDFDownload PDF

Unit 4 Syllabus PDF Download | JNTUK R20 B.Tech Artificial Intelligence Material

Knowledge representation: Introduction, approaches to knowledge representation, knowledge representation using semantic network, extended semantic networks for KR Advanced knowledge representation techniques: Introduction, conceptual dependency theory, script structure.

JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material – PDF Download
To Download The JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Unit 4 Notes PDFDownload PDF

Unit 5 Syllabus PDF Download | JNTUK R20 B.Tech Artificial Intelligence Material

Expert system and applications: Introduction phases in building expert systems, expert systems versus traditional systems, rule-based expert systems blackboard systems truth maintenance systems, application of expert systems, list of shells and tools.

JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Material – PDF Download
To Download The JNTUK R20 B.Tech CSE 3-1 Artificial Intelligence Unit 5 Notes PDFDownload PDF

JNTUK R20 B Tech CSE AI Material – Outcomes

  • Grasp the basic principles of Artificial Intelligence: Gain insight into the core ideas driving AI, including machine learning, natural language processing, and robotics.
  • Explore the practical uses of search techniques and problem-solving methods: Delve into how search strategies and problem reductions are applied in various fields such as data mining, autonomous vehicles, and game playing.
  • Utilize mathematical logic principles: Apply mathematical logic concepts like propositional and predicate logic to analyze and solve problems in AI, enhancing decision-making processes.
  • Develop methods for knowledge representation: Learn techniques to represent and organize knowledge effectively in AI systems, enabling machines to understand and manipulate information intelligently.
  • Understand Fuzzy Logic Systems: Grasp the fundamentals of fuzzy logic, a mathematical approach that deals with uncertainty and imprecision in decision-making, and explore its applications in areas such as control systems, pattern recognition, and artificial intelligence.

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