ITC703: Artificial Intelligence Syllabus for IT 7th Sem 2019 Pattern Mumbai University

Artificial Intelligence detailed syllabus scheme for Information Technology (IT), 2019 regulation has been taken from the University of Mumbai official website and presented for the Bachelor of Engineering students. For Course Code, Course Title, Test 1, Test 2, Avg, End Sem Exam, Team Work, Practical, Oral, Total, and other information, do visit full semester subjects post given below.

For all other Mumbai University Information Technology 7th Sem Syllabus 2019 Pattern, do visit IT 7th Sem 2019 Pattern Scheme. The detailed syllabus scheme for artificial intelligence is as follows.

Artificial Intelligence Syllabus for Information Technology BE 7th Sem 2019 Pattern Mumbai University

Course Objectives:

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Course Outcomes:

Students will be able to:

1. Demonstrate knowledge of the building blocks of AI as presented in terms of intelligent agents.
2. Analyze and formalize the problem as a state space, graph, design heuristics and select amongst different search or game based techniques to solve them.
3. Develop intelligent algorithms for constraint satisfaction problems and also design intelligent systems for Game Playing
4. Attain the capability to represent various real life problem domains using logic based techniques and use this to perform inference or planning.
5. Formulate and solve problems with uncertain information using Bayesian approaches.
6. Apply concept Natural Language processing to problems leading to understanding of cognitive computing. .

Prerequisites:

Programming, Data Structures.

Module I

Introduction to Intelligent Systems and Intelligent Agents Introduction to AI, AI Problems and AI techniques, Solving problems by searching, Problem Formulation. State Space Representation Structure of Intelligent agents, Types of Agents, Agent Environments PEAS representation for an Agent. 07 CO 1 CO 2

Module II

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Module III

Knowledge and Reasoning A Knowledge Based Agent, Overview of Propositional Logic, First Order Predicate Logic, Inference in First Order Predicate Logic: Forward and Backward Chaining, Resolution. 10 CO 4

Module IV

Planning Introduction to Planning, Planning with State Space Search, Partial Ordered planning, Hierarchical Planning, Conditional Planning. 06 CO 4

Module V

Uncertain Knowledge and Reasoning Uncertainly, Representing Knowledge in an Uncertain Domain, Conditional Probability, Joint Probability, Bayes theorem, Belief Networks, Simple Inference in Belief Networks. 06 CO 5

Module VI

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.
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Text Books:

1. Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 2nd Edition, Pearson Education.
2. Elaine Rich, Kevin Knight, Shivshankar B Nair, Artificial Intelligence, McGraw Hill, 3rd Edition
3. Judith S. Hurwitz, Marcia Kaufman, Adrian Bowles, Cognitive Computing and Big Data Analytics, Wiley India

Reference Books:

1. George Lugar, .AI-Structures and Strategies for Complex Problem Solving., 4/e, 2002, Pearson Education.
2. Nils J. Nilsson, Principles of Artificial Intelligence, Narosa Publication.
3. Patrick H. Winston, Artificial Intelligence, 3rd edition, Pearson Education.
4. Deepak Khemani, A First Course in Artificial Intelligence, McGraw Hill Publication
5. John Kelly , Steve Hamm, Smart Machines – IBM’s Watson and the Era of Cognitive Computing, Columbia Business School Publishing

Assessment:

Internal Assessment for 20 marks: Consisting of Two Compulsory Class Tests Approximately 40% to 50% of syllabus content must be covered in First test and remaining 40% to 50% of syllabus contents must be covered in second test. End Semester Theory Examination: Some guidelines for setting the question papers are as:

• Weightage of each module in end semester examination is expected to be/will be proportional to number of respective lecture hours mentioned in the syllabus.
• Question paper will comprise of total six questions, each carrying 20 marks.
• Q.1 will be compulsory and should cover maximum contents of the syllabus.
• Remaining question will be mixed in nature (for example if Q.2 has part
1. from module 3 then part
2. will be from any other module. (Randomly selected from all the modules)
• Total four questions need to be solved.

For detail syllabus of all other subjects of Information Technology (IT) 7th Sem 2019 regulation, visit IT 7th Sem Subjects syllabus for 2019 regulation.