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Artificial Intelligence Semester 8 (BE Fourth Year) BE Automobile Engineering University of Mumbai Topics and Syllabus

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University of Mumbai Syllabus For Semester 8 (BE Fourth Year) Artificial Intelligence: Knowing the Syllabus is very important for the students of Semester 8 (BE Fourth Year). Shaalaa has also provided a list of topics that every student needs to understand.

The University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence syllabus for the academic year 2021-2022 is based on the Board's guidelines. Students should read the Semester 8 (BE Fourth Year) Artificial Intelligence Syllabus to learn about the subject's subjects and subtopics.

Students will discover the unit names, chapters under each unit, and subtopics under each chapter in the University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Syllabus pdf 2021-2022. They will also receive a complete practical syllabus for Semester 8 (BE Fourth Year) Artificial Intelligence in addition to this.

CBCGS [2019 - current]
CBGS [2015 - 2018]
Old [2000 - 2014]

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Revised Syllabus

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence and their Unit wise marks distribution

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Course Structure 2021-2022 With Marking Scheme

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Syllabus

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Syllabus for Module 1

101 Ai and Internal Representation
  • Artificial Intelligence and the World, Representation in AI, Properties of Internal Representation, The
  • Predicate Calculus Intelligent Agents: Concept of Rational Agent, Structure of Intelligent agents, Agent Environments.
  • Problem Solving : Solving problems by searching, Problem Formulation, Search Strategies, Uninformed Search Techniques, DFS, BFS, Uniform cost search, Iterative Deepening, Comparing different Techniques, Informed search methods – Best First Search, heuristic functions, Hill Climbing, A*.IDA*. Crypt Arithmetic, Bactracking for CSP

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Syllabus for Module 2

201 Programming in Lisp Or Prolog
  • Lisps, Typing at Lisp,
  • Defining Programs,
  • Basic Flow of Control in Lisp,
  • Lisp Style,
  • Atoms and Lists,
  • Basic Debugging,
  • Building Up List Structure,
  • More on Predicates,
  • Properties, Pointers,
  • Cell Notation and the Internals (Almost) of Lisp,
  • Destructive Modification of Lists,
  • The for Function,
  • Recursion,
  • Scope of Variables Input/Output, Macros

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Syllabus for Module 3

301 Fundamentals Concepts and Models of Artificial Neural Systems
  • Biological Neuron and their Artificial Models, Models of ANN, Learning and Adaptation, Neural Networking Learning Rules.
  • Single-layer Perception Classifiers Multilayer Feed forward Networks : Linearly Nonseparable Pattern Classification, Delta Learning Rule, Feed forward Recall and Error BackPropagation Training, Learning Factor

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Syllabus for Module 4

401 Fuzzy Systems
  • Fuzzy Sets: Fuzzy Relations, Fuzzy Function, Fuzzy Measures, probabilities possibilities.
  • Fuzzy Modeling and applications of Fuzzy Control. Neural and fuzzy machine Intelligence

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Syllabus for Module 5

501 Generic Algorithm
  • Simple generic algorithm,
  • Simulation by hands,
  • similarity templates (Schemata),
  • Mathematical foundations,
  • Schema processing at work,
  • Two armed and k armed Bandit Problem,
  • Building blocks hypothesis,
  • Minimal Deceptive Problem,
  • Computer implementation of generic algorithm,
  • Data structures, Reproduction, Cross over and mutation.
  • Time to response and time to cross mapping objective function to fitness from fitness scaling.
  • Application of generic algorithm.
  • De Jong and Function Optimization.
  • Improvement in basic techniques, Improvement to genetics based machine learning, application of genetic based machine learning

University of Mumbai Semester 8 (BE Fourth Year) Artificial Intelligence Syllabus for Module 6

601 Data Mining and Information Retrieval
  • Data warehousing & Data Mining.
  • Online Analytic Processing [OLAP]: its architecture and its use.
  • Java implementations, classification trees and exploratory data analysis [EDA].
  • EDA Vs Hypothesis Testing, Computational EDA Techniques, Graphical [Data Visualization], EDA techniques for function fitting, data smoothing, layering, tessellations, contour projections, Verification of results of EDA. Applications & trends in data mining.
  • Case Studies
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