Course curriculum

    1. Introduction: About the Tutor and AI Sciences

    2. Introduction: Introduction To Instructor

    3. Introduction: Focus of the Course-Part 1

    4. Introduction: Focus of the Course- Part 2

    5. Basics of Programming: Understanding the Algorithm

    6. Basics of Programming: FlowCharts and Pseudocodes

    7. Basics of Programming: Example of Algorithms- Making Tea Problem

    8. Basics of Programming: Example of Algorithms-Searching Minimun

    9. Basics of Programming: Example of Algorithms-Searching Minimun Quiz

    10. Basics of Programming: Example of Algorithms-Searching Minimun Solution

    11. Basics of Programming: Example of Algorithms-Sorting Problem

    12. Basics of Programming: Sorting Problem in Python

    13. Why Python and Jupyter Notebook: Why Python

    14. Why Python and Jupyter Notebook: Why Jupyter Notebooks

    15. Installation of Anaconda and IPython Shell: Installing Python and Jupyter Anaconda

    16. Installation of Anaconda and IPython Shell: Your First Python Code- Hello World

    17. Installation of Anaconda and IPython Shell: Coding in IPython Shell

    18. Variable and Operator: Variables

    19. Variable and Operator: Operators

    20. Variable and Operator: Variable Name Quiz

    21. Variable and Operator: Bool Data Type in Python

    22. Variable and Operator: Comparison in Python

    23. Variable and Operator: Combining Comparisons in Python

    24. Variable and Operator: Combining Comparisons Quiz

    25. Python Useful function: Python Function- Round

    26. Python Useful function: Python Function- Round Quiz

    27. Python Useful function: Python Function- Round Solution

    28. Python Useful function: Python Function- Divmod

    29. Python Useful function: Python Function- Is instance and PowFunctions

    30. Python Useful function: Python Function- Input

    31. Control Flow in Python: If Python Condition

    32. Control Flow in Python: if Elif Else Python Conditions

    33. Control Flow in Python: if Elif Else Python Conditions Quiz

    34. Control Flow in Python: if Elif Else Python Conditions Solution

    35. Control Flow in Python: More on if Elif Else Python Conditions

    36. Control Flow in Python: More on if Elif Else Python Conditions Quiz

    37. Control Flow in Python: More on if Elif Else Python Conditions Solution

    38. Control Flow in Python: Indentations

    39. Control Flow in Python: Indentations Quiz

    40. Control Flow in Python: Indentations Solution

    41. Control Flow in Python: Comments and Problem Solving Practice With If

    42. Control Flow in Python: While Loop

    43. Control Flow in Python: While Loop break Continue

    44. Control Flow in Python: While Loop break Continue Quiz

    45. Control Flow in Python: While Loop break Continue Solution

    46. Control Flow in Python: For Loop

    47. Control Flow in Python: For Loop Quiz

    48. Control Flow in Python: For Loop Solution

    49. Control Flow in Python: Else In For Loop

    50. Control Flow in Python: Loops Practice-Sorting Problem

    51. Function and Module in Python: Functions in Python

    52. Function and Module in Python: DocString

    53. Function and Module in Python: Input Arguments

    54. Function and Module in Python: Multiple Input Arguments

    55. Function and Module in Python: Multiple Input Arguments Quiz

    56. Function and Module in Python: Multiple Input Arguments Solution

    57. Function and Module in Python: Ordering Multiple Input Arguments

    58. Function and Module in Python: Output Arguments and Return Statement

    59. Function and Module in Python: Function Practice-Output Arguments and Return Statement

    60. Function and Module in Python: Variable Number of Input Arguments

    61. Function and Module in Python: Variable Number of Input Arguments Quiz

    62. Function and Module in Python: Variable Number of Input Arguments Solution

    63. Function and Module in Python: Variable Number of Input Arguments as Dictionary

    64. Function and Module in Python: Variable Number of Input Arguments as Dictionary Quiz

    65. Function and Module in Python: Variable Number of Input Arguments as Dictionary Solution

    66. Function and Module in Python: Default Values in Python

    67. Function and Module in Python: Modules in Python

    68. Function and Module in Python: Making Modules in Python

    69. Function and Module in Python: Function Practice-Sorting List in Python

    70. String in Python: Strings

    71. String in Python: Multi Line Strings

    72. String in Python: Indexing Strings

    73. String in Python: Indexing Strings Quiz

    74. String in Python: Indexing Strings Solution

    75. String in Python: String Methods

    76. String in Python: String Methods Quiz

    77. String in Python: String Methods Solution

    78. String in Python: String Escape Sequences

    79. String in Python: String Escape Sequences Quiz

    80. String in Python: String Escape Sequences Solution

    81. Data Structure: Introduction to Data Structure

    82. Data Structure: Defining and Indexing

    83. Data Structure: Insertion and Deletion

    84. Data Structure: Insertion and Deletion Quiz

    85. Data Structure: Insertion and Deletion Solution

    86. Data Structure: Python Practice-Insertion and Deletion

    87. Data Structure: Python Practice-Insertion and Deletion Quiz

    88. Data Structure: Python Practice-Insertion and Deletion Solution

    89. Data Structure: Deep Copy or Reference Slicing

    90. Data Structure: Deep Copy or Reference Slicing Quiz

    91. Data Structure: Deep Copy or Reference Slicing Solution

    92. Data Structure: Exploring Methods Using TAB Completion

    93. Data Structure: Data Structure Abstract Ways

    94. Data Structure: Data Structure Practice

    95. Data Structure: Data Structure Practice Quiz

    96. Data Structure: Data Structure Practice Solution

    1. Introduction: Introduction to Instructor and AISciences

    2. Introduction: Introduction To Instructor

    3. Introduction: Focus of the Course

    4. Probability vs Statistics: Probability vs Statistics

    5. Sets: Definition of Set

    6. Sets: Cardinality of a Set

    7. Sets: Subsets PowerSet UniversalSet

    8. Sets: Python Practice Subsets

    9. Sets: PowerSets Solution

    10. Sets: Operations

    11. Sets: Operations Exercise 01

    12. Sets: Operations Solution 01

    13. Sets: Operations Exercise 02

    14. Sets: Operations Solution 02

    15. Sets: Operations Exercise 03

    16. Sets: Operations Solution 03

    17. Sets: Python Practice Operations

    18. Sets: VennDiagrams Operations

    19. Sets: Homework

    20. Experiment: Random Experiment

    21. Experiment: Outcome and Sample Space

    22. Experiment: Outcome and Sample Space Exercise 01

    23. Experiment: Outcome and Sample Space Solution 01

    24. Experiment: Event

    25. Experiment: Event Exercise 01

    26. Experiment: Event Solution 01

    27. Experiment: Event Exercise 02

    28. Experiment: Event Solution 02

    29. Experiment: Recap and Homework

    30. Probability Model: Probability Model

    31. Probability Model: Probability Axioms

    32. Probability Model: Probability Axioms Derivations

    33. Probability Model: Probability Axioms Derivations Exercise 01

    34. Probability Model: Probability Axioms Derivations Solution 01

    35. Probability Model: Probablility Models Example

    36. Probability Model: Probablility Models More Examples

    37. Probability Model: Probablility Models Continous

    38. Probability Model: Conditional Probability

    39. Probability Model: Conditional Probability Example

    40. Probability Model: Conditional Probability Formula

    41. Probability Model: Conditional Probability in Machine Learning

    42. Probability Model: Conditional Probability Total Probability Theorem

    43. Probability Model: Probablility Models Independence

    44. Probability Model: Probablility Models Conditional Independence

    45. Probability Model: Probablility Models Conditional Independence Exercise 01

    46. Probability Model: Probablility Models Conditional Independence Solution 01

    47. Probability Model: Probablility Models BayesRule

    48. Probability Model: Probablility Models towards Random Variables

    49. Probability Model: HomeWork

    50. Random Variables: Introduction

    51. Random Variables: Random Variables Examples

    52. Random Variables: Random Variables Examples Exercise 01

    53. Random Variables: Random Variables Examples Solution 01

    54. Random Variables: Bernulli Random Variables

    55. Random Variables: Bernulli Trail Python Practice

    56. Random Variables: Bernulli Trail Python Practice Exercise 01

    57. Random Variables: Bernulli Trail Python Practice Solution 01

    58. Random Variables: Geometric Random Variable

    59. Random Variables: Geometric Random Variable Normalization Proof Optional

    60. Random Variables: Geometric Random Variable Python Practice

    61. Random Variables: Binomial Random Variables

    62. Random Variables: Binomial Python Practice

    63. Random Variables: Random Variables in Real DataSets

    64. Random Variables: Random Variables in Real DataSets Exercise 01

    65. Random Variables: Random Variables in Real DataSets Solution 01

    66. Random Variables: Homework

    67. Continous Random Variables: Zero Probability to Individual Values

    68. Continous Random Variables: Zero Probability to Individual Values Exercise 01

    69. Continous Random Variables: Zero Probability to Individual Values Solution 01

    70. Continous Random Variables: Probability Density Functions

    71. Continous Random Variables: Probability Density Functions Exercise 01

    72. Continous Random Variables: Probability Density Functions Solution 01

    73. Continous Random Variables: Uniform Distribution

    74. Continous Random Variables: Uniform Distribution Exercise 01

    75. Continous Random Variables: Uniform Distribution Solution 01

    76. Continous Random Variables: Uniform Distribution Python

    77. Continous Random Variables: Exponential

    78. Continous Random Variables: Exponential Exercise 01

    79. Continous Random Variables: Exponential Solution 01

    80. Continous Random Variables: Exponential Python

    81. Continous Random Variables: Gaussian Random Variables

    82. Continous Random Variables: Gaussian Random Variables Exercise 01

    83. Continous Random Variables: Gaussian Random Variables Solution 01

    84. Continous Random Variables: Gaussian Python

    85. Continous Random Variables: Transformation of Random Variables

    86. Continous Random Variables: Homework

    87. Expectations: Definition

    88. Expectations: Sample Mean

    89. Expectations: Law of Large Numbers

    90. Expectations: Law of Large Numbers Famous Distributions

    91. Expectations: Law of Large Numbers Famous Distributions Python

    92. Expectations: Variance

    93. Expectations: Homework

    94. Project Bayes Classifier: Project Bayes Classifier From Scratch

    95. Multiple Random Variables: Joint Distributions

    96. Multiple Random Variables: Joint Distributions Exercise 01

    97. Multiple Random Variables: Joint Distributions Solution 01

    98. Multiple Random Variables: Joint Distributions Exercise 02

    99. Multiple Random Variables: Joint Distributions Solution 02

    100. Multiple Random Variables: Joint Distributions Exercise 03

    101. Multiple Random Variables: Joint Distributions Solution 03

    102. Multiple Random Variables: Multivariate Gaussian

    103. Multiple Random Variables: Conditioning Independence

    104. Multiple Random Variables: Classification

    105. Multiple Random Variables: Naive Bayes Classification

    106. Multiple Random Variables: Regression

    107. Multiple Random Variables: Curse of Dimensionality

    108. Multiple Random Variables: Homework

    109. Optional Estimation: Parametric Distributions

    110. Optional Estimation: MLE

    111. Optional Estimation: LogLiklihood

    112. Optional Estimation: MAP

    113. Optional Estimation: Logistic Regression

    114. Optional Estimation: Ridge Regression

    115. Optional Estimation: DNN

    116. Mathematical Derivations for Math Lovers: Permutations

    117. Mathematical Derivations for Math Lovers: Combinations

    118. Mathematical Derivations for Math Lovers: Binomial Random Variable

    119. Mathematical Derivations for Math Lovers: Logistic Regression Formulation

    120. Mathematical Derivations for Math Lovers: Logistic Regression Derivation

    1. Introduction: Course Introduction

    2. Introduction: AI Sciences

    3. Introduction: Course Outline

    4. Summary Statistics: Module Intoduction

    5. Summary Statistics: Overview

    6. Summary Statistics: Summary Statistics

    7. Summary Statistics: Average Types

    8. Summary Statistics: Mean

    9. Summary Statistics: Median

    10. Summary Statistics: Median Example

    11. Summary Statistics: Mode

    12. Summary Statistics: Case Study For Average

    13. Summary Statistics: IQR

    14. Summary Statistics: Variance

    15. Summary Statistics: Standard Deviation

    16. Summary Statistics: Averages in Python

    17. Summary Statistics: Std Deviation and Variance in Python

    18. Summary Statistics: IQR in Python

    19. Hypothesis Testing: Module Introduction

    20. Hypothesis Testing: Hypothesis Testing Overview

    21. Hypothesis Testing: Terminologies in Hypothesis Testing

    22. Hypothesis Testing: Null Hypothesis

    23. Hypothesis Testing: Alternate Hypothesis

    24. Hypothesis Testing: Test Statistics

    25. Hypothesis Testing: P-Value

    26. Hypothesis Testing: Critical Value

    27. Hypothesis Testing: Level of Significance

    28. Hypothesis Testing: Case Study 1

    29. Hypothesis Testing: Case Study 2

    30. Hypothesis Testing: Calculations for Python

    31. Hypothesis Testing: Steps of Hypothesis Testing

    32. Hypothesis Testing: Code Outcomes

    33. Hypothesis Testing: Calculation of Z in Python

    34. Hypothesis Testing: Norm Function

    35. Hypothesis Testing: P Value Python

    36. Correlation and Regression: Module Introduction

    37. Correlation and Regression: Covariance and Correlation

    38. Correlation and Regression: Correlation

    39. Correlation and Regression: Regression

    40. Correlation and Regression: Correlation and Covariance in Python

    41. Correlation and Regression: Entering Input

    42. Correlation and Regression: Linear Regression Results

    43. Multiple Regression: Module Overview

    44. Multiple Regression: Motivation for Multiple Regression

    45. Multiple Regression: Formula for MR

    46. Multiple Regression: Preparing the Data

    47. Multiple Regression: Multiple Regression in Python

About this course

  • $199.99
  • 263 lessons
  • 28 hours of video content