Prospective candidates interested in the MSc in Cognitive Science program at CBCS, AU are required to take the Cognitive Science Joint Entrance Test (COGJET).
COGJET is a joint entrance test for admission into post graduate programs in cognitive sciences at CBCS University of Allahabad, Chandigarh University, IIIT Hyderabad, IIT Delhi, IIT Kanpur and Panjab University.
Syllabus and Reading List
Part I questions will be approximately at the same level as the CAT (Common Admission Test) for admission to management programs.
The syllabus and reading list for each section in Part II is given below. The resources in the suggested reading lists contain much more material than required by the syllabus. Study only the relevant parts. Also, note that other equally good resources are available in print and digital form and you can use those as well.
Mathematics for Computer Science:
- Discrete Maths (Boolean Algebra, Propositional Logic, Set, Relation, Function, Recurrences, Permutations and Combinations.)
- Linear Algebra (Matrices and Determinants)
- Basic Calculus (Limit, continuity, differentiability, extrema, maxima, minima, differentiation and integration, integration as area under the curve)
- Probability and Statistics (Elementary probability theory, Conditional probability, Bayes theorem, Random Variables, Simple discrete and Continuous Distributions, expectation, mean, variance, median, percentiles.)
- Basic Programming (variables, types, declarations, assignment, conditionals, iteration, recursion, functions. (Familiarity with programming and pseudo code is needed but specific programming language questions will not be asked.)
- Basic data structures and Algorithms (Arrays, Sorting, Searching, HCF, LCM, prime finding, similar number based algorithms.).
TH Cormen, CE Leiserson, RL Rivest, C Stein, Introduction to Algorithms, 3rd Ed., MIT Press, 2009. (Indian edition is available).
C Hamacher, S Vrosenic, S Zaky, Computer Organization, 5th Ed. McGraw Hill 2011. (Indian edition is available).
Elementary psychology and basics of hypothesis testing:
- Basic neuroanatomy (Physical layout of the brain, names of important components and their functions, e.g. cortex, cerebellum, brainstem, neuron Structure, components, action potentials, synapses, nervous system, receptors, connectivity, speed, structure etc.)
- Psychophysics (absolute and difference thresholds, Weber’s law, Fechner’s Law.)
- Learning (Associative and non-associative learning, Pavlovian conditioning, Hebbian learning.)
- Memory (modal model of memory, working memory, phonological loop, visuo-spatial sketchpad, central executive, types of memory (explicit, implicit), memory inhibition effects, e.g. blocking, interference etc. Long-term memory: encoding, retrieval, forgetting.)
- Visual perception: (basics of color, depth and motion perception, perceptual constancy, and principles of perceptual organization.)
- Basics of hypothesis testing (e.g. t-test, chi-square, ANOVA), significance, p-value, error types, power and size effects.
Clifford Morgan, Richard King (2017) Introduction to Psychology. 7th Edition. McGraw Hill.
Stangor (2010). MIT – Introduction to Psychology (Open Source – free to download on the internet)
David G. Myers. 2017. Psychology. Macmillan Indian Edition.
Cohen, B.H. (2014) Explaining Psychological Statistics. 4th Ed. John Wiley & Sons.
Mangal, S.K. (2004) Statistics in Psychology and Education. 2nd Ed. Prentice Hall India.
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