Course12710400360 lectures
Mathematical Tools for Cognitive Science
Prof. Himanshu Yadav · IIT Kanpur
About
This is a foundational course on Mathematics intended for students of Cognitive Science, Cognitive Systems, Psychology, and Linguistics. We are going to cover the following topics:. functions, differentiation, Matrix and Vector Algebra, Integration, multivariate calculus, and sets, probability, and random variables.
Intended audience: Cognitive Science students, Psychology students, Linguistics students, Biological and Neuroscience students
Lectures
Week 1
- Lecture 01: Real numbers and Exponents
- Lecture 02: Equations
- Lecture 03: Graphs
- Lecture 04: Graphs and Equations
- Lecture 05: Functions
Week 2
- Lecture 06: Inverse Functions
- Lecture 07: Graphs of Inverse Functions
- Lecture 08: Exponential Functions
- Lecture 09: Logarithmic Functions
- Lecture 10: Applications of Logarithmic and Exponential Functions
Week 3
- Lecture 11: Introduction to Trigonometric Functions
- Lecture 12: Sine and Cosine Functions
- Lecture 13: Trigonometric Identities
- Lecture 14: Trigonometric Identities: Examples
- Lecture 15: Representation of a point in a plane
Week 4
- Lecture 16: Introduction to Differentiation
- Lecture 17: Derivative of a Function
- Lecture 18: Some Basic Derivatives
- Lecture 19: Differentiation Examples
- Lecture 20: Practice Problems on Differentiation
Week 5
- Lecture 21: Maxima and Minima of a Function
- Lecture 22: Maxima and Minima examples
- Lecture 23: Partial Derivative
- Lecture 24: Least Squares Method
- Lecture 25: Differentiation Applications
Week 6
- Lecture 26: Introduction to Matrices
- Lecture 27: Matrix Operations
- Lecture 28: Inverse Matrix
- Lecture 29: Introduction to Vectors
- Lecture 30: Dot Product and Cross Product
Week 7
- Lecture 31: Introduction to Integration
- Lecture 32: Some Basic Integrals
- Lecture 33: Integration Examples
- Lecture 34: Substitution Method of Integration
- Lecture 35: Integration by Parts
Week 8
- Lecture 36: Introduction to Sets
- Lecture 37: Operations on Sets
- Lecture 38: Properties of Sets
- Lecture 39: Algebra of Sets
- Lecture 40: Sets and Probability
Week 9
- Lecture 41: Introduction to Probability
- Lecture 42: Probability Axioms
- Lecture 43: Probability Corollaries
- Lecture 44: Conditional Probability
- Lecture 45: Probability Examples
Week 10
- Lecture 46: Introduction to Random Variables
- Lecture 47: Discrete and Continuous Random Variables
- Lecture 48: Binomial and Poisson Distributions
- Lecture 49: Normal and Lognormal Distributions
- Lecture 50: Other Continuous Random Variables
Week 11
- Lecture 51: Probability Distributions in R
- Lecture 52: Continuous Random Variables in R
- Lecture 53: Random Variables Examples in R
- Lecture 54: Likelihood Function
- Lecture 55: Likelihood Function in R
Week 12
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Kanpur
- Department
- Multidisciplinary
- Teacher
- Prof. Himanshu Yadav
- Level
- Undergraduate
- Language
- English
- Subjects
- Mathematics, Psychology and the brain
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed
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