Course curriculum

  • 1

    Introduction to Course

    • Introduction to Instructor and AISciences
    • Focus of the Course
  • 2

    Probability vs Statistics

    • Probability vs Statistics
  • 3

    Sets

    • Definition of Set
    • Cardinality of a Set
    • Subsets PowerSet UniversalSet
    • Python Practice Subsets
    • PowerSets Solution
    • Operations
    • Python Practice Operations
    • VennDiagrams Operations
    • Homework
  • 4

    Experiment

    • Random Experiment
    • Outcome and Sample Space
    • Event
    • Recap and Homework
  • 5

    Probability Model

    • Probability Model
    • Probability Axioms
    • Probability Axioms Derivations
    • Probablility Models Example
    • Probablility Models More Examples
    • Probablility Models Continous
    • Conditional Probability
    • Conditional Probability Example
    • Conditional Probability Formula
    • Conditional Probability in Machine Learning
    • Conditional Probability Total Probability Theorem
    • Probablility Models Independence
    • Probablility Models Conditional Independence
    • Probablility Models BayesRule
    • Probablility Models towards Random Variables
    • HomeWork
  • 6

    Random Variables

    • Introduction
    • Random Variables Examples
    • Bernulli Random Variables
    • Bernulli Trail Python Practice
    • Geometric Random Variable
    • Geometric Random Variable Normalization Proof Optional
    • Geometric Random Variable Python Practice
    • Binomial Random Variables
    • Binomial Python Practice
    • Random Variables in Real DataSets
    • Homework
  • 7

    Continous Random Variables

    • Zero Probability to Individual Values
    • Probability Density Functions
    • Uniform Distribution
    • Uniform Distribution Python
    • Exponential
    • Exponential Python
    • Gaussian Random Variables
    • Gaussian Python
    • Transformation of Random Variables
    • Homework
  • 8

    Expectations

    • Definition
    • Sample Mean
    • Law of Large Numbers
    • Law of Large Numbers Famous Distributions
    • Law of Large Numbers Famous Distributions Python
    • Variance
    • Homework
  • 9

    Project Bayes Classifier

    • Project Bayes Classifier From Scratch
  • 10

    Multiple Random Variables

    • Joint Distributions
    • Multivariate Gaussian
    • Conditioning Independence
    • Classification
    • Naive Bayes Classification
    • Regression
    • Curse of Dimensionality
    • Homework
  • 11

    Optional Estimation

    • Parametric Distributions
    • MLE
    • LogLiklihood
    • MAP
    • Logistic Regression
    • Ridge Regression
    • DNN
  • 12

    Mathematical Derivations for Math Lovers (Optional)

    • Permutations
    • Combinations
    • Binomial Random Variable
    • Logistic Regression Formulation
    • Logistic Regression Derivation