CCS337: Cognitive Science syllabus for AI&DS 2021 regulation (Professional Elective-VII)

Cognitive Science detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the AI&DS students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Artificial Intelligence & Data Science 6th Sem scheme and its subjects, do visit AI&DS 6th Sem 2021 regulation scheme. For Professional Elective-VII scheme and its subjects refer to AI&DS Professional Elective-VII syllabus scheme. The detailed syllabus of cognitive science is as follows.

Course Objectives:

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Unit I

PHILOSOPHY, PSYCHOLOGY AND NEUROSCIENCE
Philosophy: Mental-physical Relation – From Materialism to Mental Science – Logic and the Sciences of the Mind – Psychology: Place of Psychology within Cognitive Science – Science of Information Processing -Cognitive Neuroscience – Perception – Decision – Learning and Memory – Language Understanding and Processing.

Unit II

COMPUTATIONAL INTELLIGENCE
Machines and Cognition – Artificial Intelligence – Architectures of Cognition – Knowledge Based Systems – Logical Representation and Reasoning – Logical Decision Making -Learning -Language – Vision.

Unit III

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Unit IV

INFERENCE MODELS OF COGNITION
Generative Models – Conditioning – Causal and statistical dependence – Conditional dependence – Data Analysis – Algorithms for Inference.

Unit V

LEARNING MODELS OF COGNITION
Learning as Conditional Inference – Learning with a Language of Thought – Hierarchical Models-Learning (Deep) Continuous Functions – Mixture Models.

Practical Exercises

1. Demonstration of Mathematical functions using WebPPL.
2. Implementation of reasoning algorithms.
3. Developing an Application system using generative model.
4. Developing an Application using conditional inference learning model.
5. Application development using hierarchical model.
6. Application development using Mixture model.

Course Outcomes:

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Text Books:

1. Vijay V Raghavan,Venkat N.Gudivada, VenuGovindaraju, C.R. Rao, Cognitive Computing: Theory and Applications: (Handbook of Statistics 35), Elsevier publications, 2016
2. Judith Hurwitz, Marcia Kaufman, Adrian Bowles, Cognitive Computing and Big Data Analytics, Wiley Publications, 2015
3. Robert A. Wilson, Frank C. Keil, “The MIT Encyclopedia of the Cognitive Sciences”,The MIT Press, 1999.
4. Jose Luis Bermudez, Cognitive Science -An Introduction to the Science of the Mind, Cambridge University Press 2020

Reference Books:

1. Noah D. Goodman, Andreas Stuhlmuller, “The Design and Implementation of Probabilistic Programming Languages”, Electronic version of book
• https://dippl.org/.
2. Noah D. Goodman, Joshua B. Tenenbaum, The ProbMods Contributors, “Probabilistic Models of Cognition”, Second Edition, 2016
• https://probmods.org/.

For detailed syllabus of all the other subjects of Artificial Intelligence & Data Science 6th Sem, visit AI&DS 6th Sem subject syllabuses for 2021 regulation.

For all Artificial Intelligence & Data Science results, visit Anna University AI&DS all semester results direct link.