Artificial Intelligence Deep Learning detailed syllabus scheme for Electronics & Telecommunication Engineering (ET), 2020-21 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below.
For 7th Sem Scheme of Electronics & Telecommunication Engineering (ET), 2020-21 Onwards, do visit ET 7th Sem Scheme, 2020-21 Onwards. For the Elective-IV Labs scheme of 7th Sem 2020-21 onwards, refer to ET 7th Sem Elective-IV Labs Scheme 2020-21 Onwards. The detail syllabus for artificial intelligence deep learning is as follows.
Artificial Intelligence Deep Learning Syllabus for Electronics & Telecommunication Engineering (ET) 4th Year 7th Sem 2020-21 DBATU
Course Objectives:
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Course Outcomes:
This course will enable students to
- Identify the AI based problems.
- Apply techniques to solve the AI problems.
- Define learning and explain various logic inferences.
- Discuss different learning techniques.
UNIT – 1
Introduction: What Is AI? Thinking humanly: The cognitive modeling approach. Thinking rationally: The laws of thought approach, Acting rationally: The rational agent approach. The Foundations of Artificial Intelligence, Mathematics, Economics, Neuroscience, Computer engineering, The History of Artificial Intelligence. AI becomes an industry (1980– present). Agents and Environments, Good Behaviour: The Concept of Rationality. The Nature of Environments. The Structure of Agents.
UNIT – 2
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UNIT – 3
Game Playing: Games, Optimal Decisions in Games, The minimax algorithm, Optimal decisions in multiplayer games, Alpha Beta Pruning, Move ordering, Imperfect Real-Time Decisions, Cutting off search, Forward pruning, Stochastic Games, Evaluation functions for games of chance, Partially Observable Games, Krieg spiel: Partially observable chess, Card games, State-of-the-Art Game Programs, Alternative Approaches.
UNIT – 4
Logic and inference: Defining Constraint Satisfaction Problems, Constraint Propagation: Inference in CSPs, Backtracking Search for CSPs, Local Search for CSPs, The Structure of Problems, Knowledge-Based Agents, The Wumpus World, Logic , Propositional Logic: A Very Simple Logic, Propositional Theorem Proving, Effective Propositional Model Checking, Agents Based on Propositional Logic. Forward Chaining, Backward Chaining, Definition of Classical Planning. Algorithms for Planning as State-Space Search, Planning Graphs.
UNIT – 5
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier..
Text Books:
- Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach. III Edition
- E. Rich, K. Knight & S. B. Nair – Artificial Intelligence, 3/e, McGraw Hill.
- Dan W. Patterson, Introduction to Artificial Intelligence and Expert Systems, Prentice Hal of India.
- G. Luger, Artificial Intelligence: Structures and Strategies for complex problem Solving, Fourth Edition, Pearson Education, 2002.
- N.P. Padhy Artificial Intelligence and Intelligent Systems , Oxford UniversityPress-2015.
For detail syllabus of all subjects of Electronics & Telecommunication Engineering (ET) 7th Sem 2020-21 onwards, visit ET 7th Sem Subjects of 2020-21 Onwards.