Cognitive Computing detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the IT 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 Information Technology 7th Sem scheme and its subjects, do visit IT 7th Sem 2019 regulation scheme. For Professional Elective-IV scheme and its subjects refer to IT Professional Elective-IV syllabus scheme. The detailed syllabus of cognitive computing is as follows.
Course Objective:
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Unit I
Philosophy, Psychology and Neuroscience
Philosophy: Mental-physical Relation – From Materialism to Mental Science – Detour before the naturalistic turn – The Philosophy of Science – The Mind in Cognitive Science – Logic and the Sciences of the Mind – Psychology: Place of Psychology within Cognitive Science -Science of Information Processing – Neurosciences: Cognitive Neuroscience – Perception -Decision – Learning and Memory – Language Understanding and Processing.
Suggested Activities:
- Flipped classroom on logic and sciences in the mind.
- Case study on how philosophy (western and eastern), pychology and neuroscience (thought process in normal persons, children and differently-abled) helps in cognition.
- Mindmap of cognition with various attributes such as mind, logic, information processing etc.
- Discussion and debate on cognition.
Suggested Evaluation Methods:
- Quiz on logic and sciences in the mind.
- Active discussion on the case study and how the factors such as learning and memory affect cognition.
- Essay writing on how various factors influence cognition.
Unit II
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Unit III
Probabilistic Programming Language
WebPPL Language – Syntax – Using Javascript Libraries – Manipulating probability types and distributions – Finding Inference – Exploring random computation – Coroutines: Functions that receive continuations -Enumeration – Other basic computation.
Suggested Activities:
- Flipped classroom on Javascript libraries.
- Exploring the existing mathematical models.
- Practical – Programming the common mathematical functions using PPL.
Suggested Evaluation Methods:
- Quiz on the basics of Javascript and WebPPL.
- Practical – Programming assignment on developing miniature programs using WebPPL for inference mechanisms.
- Evaluation of the programming assignments.
Unit IV
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Unit V
Implementing the Learning Models of Cognition
Learning as Conditional Inference – Learning with a Language of Thought – Hierarchical Models – Occam”s Razor – Learning (Deep) Continuous Functions – Mixture Models.
Suggested Activities:
- Flipped classroom on mixture models.
- Perform sample calculation of models manually.
Suggested Evaluation Methods:
- Quiz on mixture models.
- Practical – Automate the mathematical functions through WebPPL.
- Practical – Programming assignment on learning models for continuous functions.
- Evaluation of the programming assignments.
Course Outcome:
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 pdfs platform to make students’s lives easier..
Text Books:
- Robert A. Wilson, Frank C. Keil, “The MIT Encyclopedia of the Cognitive Sciences”, The MIT Press, 1999.
References:
- Noah D. Goodman, Andreas Stuhlmuller, “The Design and Implementation of Probabilistic Programming Languages”, Electronic version of book, https://dippl.org/.
- 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 Information Technology 7th Sem, visit IT 7th Sem subject syllabuses for 2019 regulation.
For all Information Technology results, visit Anna University IT all semester results direct link.