Python Mastery for Data, Statistics & Statistical Modeling

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AI Sciences,AI Sciences Team

28:08:07

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1 - Python for Data Science and Data Analysis

1 - Link to the Python codes for the projects and the data.html

2 - Introduction About the Tutor and AI Sciences.mp4

11:54

3 - Introduction Introduction To Instructor.mp4

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4 - Introduction Focus of the CoursePart 1.mp4

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5 - Introduction Focus of the Course Part 2.mp4

07:41

6 - Basics of Programming Understanding the Algorithm.mp4

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7 - Basics of Programming FlowCharts and Pseudocodes.mp4

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8 - Basics of Programming Example of Algorithms Making Tea Problem.mp4

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9 - Basics of Programming Example of AlgorithmsSearching Minimun.mp4

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10 - Basics of Programming Example of AlgorithmsSearching Minimun Quiz.mp4

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11 - Basics of Programming Example of AlgorithmsSorting Problem.mp4

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12 - Basics of Programming Example of AlgorithmsSearching Minimun Solution.mp4

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13 - Basics of Programming Sorting Problem in Python.mp4

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14 - Why Python and Jupyter Notebook Why Python.mp4

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15 - Why Python and Jupyter Notebook Why Jupyter Notebooks.mp4

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16 - Installation of Anaconda and IPython Shell Installing Python and Jupyter Anaconda.mp4

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17 - Installation of Anaconda and IPython Shell Your First Python Code Hello World.mp4

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18 - Installation of Anaconda and IPython Shell Coding in IPython Shell.mp4

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19 - Variable and Operator Variables.mp4

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20 - Variable and Operator Operators.mp4

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21 - Variable and Operator Variable Name Quiz.mp4

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22 - Variable and Operator Bool Data Type in Python.mp4

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23 - Variable and Operator Comparison in Python.mp4

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24 - Variable and Operator Combining Comparisons in Python.mp4

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25 - Variable and Operator Combining Comparisons Quiz.mp4

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26 - Python Useful function Python Function Round.mp4

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27 - Python Useful function Python Function Round Quiz.mp4

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28 - Python Useful function Python Function Round Solution.mp4

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29 - Python Useful function Python Function Divmod.mp4

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30 - Python Useful function Python Function Is instance and PowFunctions.mp4

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31 - Python Useful function Python Function Input.mp4

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32 - Control Flow in Python If Python Condition.mp4

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33 - Control Flow in Python if Elif Else Python Conditions.mp4

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34 - Control Flow in Python if Elif Else Python Conditions Quiz.mp4

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35 - Control Flow in Python if Elif Else Python Conditions Solution.mp4

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36 - Control Flow in Python More on if Elif Else Python Conditions.mp4

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37 - Control Flow in Python More on if Elif Else Python Conditions Quiz.mp4

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38 - Control Flow in Python More on if Elif Else Python Conditions Solution.mp4

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39 - Control Flow in Python Indentations.mp4

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40 - Control Flow in Python Indentations Quiz.mp4

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41 - Control Flow in Python Indentations Solution.mp4

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42 - Control Flow in Python Comments and Problem Solving Practice With If.mp4

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43 - Control Flow in Python While Loop.mp4

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44 - Control Flow in Python While Loop break Continue.mp4

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45 - Control Flow in Python While Loop break Continue Quiz.mp4

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46 - Control Flow in Python While Loop break Continue Solution.mp4

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47 - Control Flow in Python For Loop.mp4

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48 - Control Flow in Python For Loop Quiz.mp4

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49 - Control Flow in Python For Loop Solution.mp4

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50 - Control Flow in Python Else In For Loop.mp4

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51 - Control Flow in Python Loops PracticeSorting Problem.mp4

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52 - Function and Module in Python Functions in Python.mp4

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53 - Function and Module in Python DocString.mp4

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54 - Function and Module in Python Input Arguments.mp4

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55 - Function and Module in Python Multiple Input Arguments.mp4

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56 - Function and Module in Python Multiple Input Arguments Quiz.mp4

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57 - Function and Module in Python Multiple Input Arguments Solution.mp4

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58 - Function and Module in Python Ordering Multiple Input Arguments.mp4

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59 - Function and Module in Python Output Arguments and Return Statement.mp4

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60 - Function and Module in Python Function PracticeOutput Arguments and Return Statement.mp4

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61 - Function and Module in Python Variable Number of Input Arguments.mp4

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62 - Function and Module in Python Variable Number of Input Arguments Quiz.mp4

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63 - Function and Module in Python Variable Number of Input Arguments Solution.mp4

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64 - Function and Module in Python Variable Number of Input Arguments as Dictionary.mp4

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65 - Function and Module in Python Variable Number of Input Arguments as Dictionary Quiz.mp4

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66 - Function and Module in Python Variable Number of Input Arguments as Dictionary Solution.mp4

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67 - Function and Module in Python Default Values in Python.mp4

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68 - Function and Module in Python Modules in Python.mp4

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69 - Function and Module in Python Making Modules in Python.mp4

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70 - Function and Module in Python Function PracticeSorting List in Python.mp4

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71 - String in Python Strings.mp4

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72 - String in Python Multi Line Strings.mp4

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73 - String in Python Indexing Strings.mp4

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74 - String in Python Indexing Strings Quiz.mp4

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75 - String in Python Indexing Strings Solution.mp4

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76 - String in Python String Methods.mp4

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77 - String in Python String Methods Quiz.mp4

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78 - String in Python String Methods Solution.mp4

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79 - String in Python String Escape Sequences.mp4

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80 - String in Python String Escape Sequences Quiz.mp4

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81 - String in Python String Escape Sequences Solution.mp4

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82 - Data Structure Introduction to Data Structure.mp4

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83 - Data Structure Defining and Indexing.mp4

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84 - Data Structure Insertion and Deletion.mp4

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85 - Data Structure Insertion and Deletion Quiz.mp4

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86 - Data Structure Insertion and Deletion Solution.mp4

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87 - Data Structure Python PracticeInsertion and Deletion.mp4

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88 - Data Structure Python PracticeInsertion and Deletion Quiz.mp4

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89 - Data Structure Python PracticeInsertion and Deletion Solution.mp4

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90 - Data Structure Deep Copy or Reference Slicing.mp4

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91 - Data Structure Deep Copy or Reference Slicing Quiz.mp4

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92 - Data Structure Deep Copy or Reference Slicing Solution.mp4

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93 - Data Structure Exploring Methods Using TAB Completion.mp4

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94 - Data Structure Data Structure Abstract Ways.mp4

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95 - Data Structure Data Structure Practice.mp4

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96 - Data Structure Data Structure Practice Quiz.mp4

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97 - Data Structure Data Structure Practice Solution.mp4

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2 - Mastering Probability Statistic Python Theory Projects

98 - Link to the Python codes for the projects and the data.html

99 - Introduction Introduction to Instructor and AISciences.mp4

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100 - Introduction Introduction To Instructor.mp4

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101 - Introduction Focus of the Course.mp4

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102 - Probability vs Statistics Probability vs Statistics.mp4

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103 - Sets Definition of Set.mp4

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104 - Sets Cardinality of a Set.mp4

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105 - Sets Subsets PowerSet UniversalSet.mp4

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106 - Sets Python Practice Subsets.mp4

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107 - Sets PowerSets Solution.mp4

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108 - Sets Operations.mp4

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109 - Sets Operations Exercise 01.mp4

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115 - Sets Python Practice Operations.mp4

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116 - Sets VennDiagrams Operations.mp4

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117 - Sets Homework.mp4

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118 - Experiment Random Experiment.mp4

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119 - Experiment Outcome and Sample Space.mp4

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120 - Experiment Outcome and Sample Space Exercise 01.mp4

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121 - Experiment Outcome and Sample Space Solution 01.mp4

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122 - Experiment Event.mp4

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123 - Experiment Event Exercise 01.mp4

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124 - Experiment Event Solution 01.mp4

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125 - Experiment Event Exercise 02.mp4

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126 - Experiment Event Solution 02.mp4

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127 - Experiment Recap and Homework.mp4

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128 - Probability Model Probability Model.mp4

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129 - Probability Model Probability Axioms.mp4

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130 - Probability Model Probability Axioms Derivations.mp4

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131 - Probability Model Probability Axioms Derivations Exercise 01.mp4

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132 - Probability Model Probability Axioms Derivations Solution 01.mp4

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133 - Probability Model Probablility Models Example.mp4

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134 - Probability Model Probablility Models More Examples.mp4

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135 - Probability Model Probablility Models Continous.mp4

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136 - Probability Model Conditional Probability.mp4

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137 - Probability Model Conditional Probability Example.mp4

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138 - Probability Model Conditional Probability Formula.mp4

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139 - Probability Model Conditional Probability in Machine Learning.mp4

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140 - Probability Model Conditional Probability Total Probability Theorem.mp4

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141 - Probability Model Probablility Models Independence.mp4

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142 - Probability Model Probablility Models Conditional Independence.mp4

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143 - Probability Model Probablility Models Conditional Independence Exercise 01.mp4

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144 - Probability Model Probablility Models Conditional Independence Solution 01.mp4

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145 - Probability Model Probablility Models BayesRule.mp4

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146 - Probability Model Probablility Models towards Random Variables.mp4

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147 - Probability Model HomeWork.mp4

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148 - Random Variables Introduction.mp4

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149 - Random Variables Random Variables Examples.mp4

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150 - Random Variables Random Variables Examples Exercise 01.mp4

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151 - Random Variables Random Variables Examples Solution 01.mp4

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152 - Random Variables Bernulli Random Variables.mp4

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153 - Random Variables Bernulli Trail Python Practice.mp4

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154 - Random Variables Bernulli Trail Python Practice Exercise 01.mp4

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155 - Random Variables Bernulli Trail Python Practice Solution 01.mp4

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156 - Random Variables Geometric Random Variable.mp4

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157 - Random Variables Geometric Random Variable Normalization Proof Optional.mp4

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158 - Random Variables Geometric Random Variable Python Practice.mp4

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159 - Random Variables Binomial Random Variables.mp4

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160 - Random Variables Binomial Python Practice.mp4

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161 - Random Variables Random Variables in Real DataSets.mp4

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162 - Random Variables Random Variables in Real DataSets Exercise 01.mp4

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163 - Random Variables Random Variables in Real DataSets Solution 01.mp4

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164 - Random Variables Homework.mp4

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165 - Continous Random Variables Zero Probability to Individual Values.mp4

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166 - Continous Random Variables Zero Probability to Individual Values Exercise 01.mp4

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167 - Continous Random Variables Zero Probability to Individual Values Solution 01.mp4

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168 - Continous Random Variables Probability Density Functions.mp4

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169 - Continous Random Variables Probability Density Functions Exercise 01.mp4

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170 - Continous Random Variables Probability Density Functions Solution 01.mp4

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171 - Continous Random Variables Uniform Distribution.mp4

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172 - Continous Random Variables Uniform Distribution Exercise 01.mp4

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173 - Continous Random Variables Uniform Distribution Solution 01.mp4

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174 - Continous Random Variables Uniform Distribution Python.mp4

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175 - Continous Random Variables Exponential.mp4

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176 - Continous Random Variables Exponential Exercise 01.mp4

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177 - Continous Random Variables Exponential Solution 01.mp4

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178 - Continous Random Variables Exponential Python.mp4

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179 - Continous Random Variables Gaussian Random Variables.mp4

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180 - Continous Random Variables Gaussian Random Variables Exercise 01.mp4

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181 - Continous Random Variables Gaussian Random Variables Solution 01.mp4

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182 - Continous Random Variables Gaussian Python.mp4

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183 - Continous Random Variables Transformation of Random Variables.mp4

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184 - Continous Random Variables Homework.mp4

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185 - Expectations Definition.mp4

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186 - Expectations Sample Mean.mp4

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187 - Expectations Law of Large Numbers.mp4

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188 - Expectations Law of Large Numbers Famous Distributions.mp4

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189 - Expectations Law of Large Numbers Famous Distributions Python.mp4

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190 - Expectations Variance.mp4

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191 - Expectations Homework.mp4

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192 - Project Bayes Classifier Project Bayes Classifier From Scratch.mp4

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193 - Multiple Random Variables Joint Distributions.mp4

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194 - Multiple Random Variables Joint Distributions Exercise 01.mp4

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195 - Multiple Random Variables Joint Distributions Solution 01.mp4

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196 - Multiple Random Variables Joint Distributions Exercise 02.mp4

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197 - Multiple Random Variables Joint Distributions Solution 02.mp4

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198 - Multiple Random Variables Joint Distributions Exercise 03.mp4

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199 - Multiple Random Variables Joint Distributions Solution 03.mp4

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200 - Multiple Random Variables Multivariate Gaussian.mp4

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201 - Multiple Random Variables Conditioning Independence.mp4

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202 - Multiple Random Variables Classification.mp4

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203 - Multiple Random Variables Naive Bayes Classification.mp4

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204 - Multiple Random Variables Regression.mp4

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205 - Multiple Random Variables Curse of Dimensionality.mp4

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206 - Multiple Random Variables Homework.mp4

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207 - Optional Estimation Parametric Distributions.mp4

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208 - Optional Estimation MLE.mp4

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209 - Optional Estimation LogLiklihood.mp4

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210 - Optional Estimation MAP.mp4

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211 - Optional Estimation Logistic Regression.mp4

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212 - Optional Estimation Ridge Regression.mp4

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213 - Optional Estimation DNN.mp4

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214 - Mathematical Derivations for Math Lovers Permutations.mp4

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215 - Mathematical Derivations for Math Lovers Combinations.mp4

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216 - Mathematical Derivations for Math Lovers Binomial Random Variable.mp4

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217 - Mathematical Derivations for Math Lovers Logistic Regression Formulation.mp4

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218 - Mathematical Derivations for Math Lovers Logistic Regression Derivation.mp4

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219 - THANK YOU.mp4

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3 - Statistics Statistical Modeling Made Easy for ALL

220 - Link to the Python codes for the projects and the data.html

221 - Introduction Course Introduction.mp4

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222 - Introduction AI Sciences.mp4

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223 - Introduction Course Outline.mp4

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224 - Summary Statistics Module Intoduction.mp4

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225 - Summary Statistics Overview.mp4

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226 - Summary Statistics Summary Statistics.mp4

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227 - Summary Statistics Average Types.mp4

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228 - Summary Statistics Mean.mp4

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229 - Summary Statistics Median.mp4

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230 - Summary Statistics Median Example.mp4

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231 - Summary Statistics Mode.mp4

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232 - Summary Statistics Case Study For Average.mp4

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233 - Summary Statistics IQR.mp4

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234 - Summary Statistics Variance.mp4

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235 - Summary Statistics Standard Deviation.mp4

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236 - Summary Statistics Averages in Python.mp4

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237 - Summary Statistics Std Deviation and Variance in Python.mp4

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238 - Summary Statistics IQR in Python.mp4

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239 - Hypothesis Testing Module Introduction.mp4

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240 - Hypothesis Testing Hypothesis Testing Overview.mp4

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241 - Hypothesis Testing Terminologies in Hypothesis Testing.mp4

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242 - Hypothesis Testing Null Hypothesis.mp4

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243 - Hypothesis Testing Alternate Hypothesis.mp4

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244 - Hypothesis Testing Test Statistics.mp4

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245 - Hypothesis Testing PValue.mp4

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246 - Hypothesis Testing Critical Value.mp4

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247 - Hypothesis Testing Level of Significance.mp4

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248 - Hypothesis Testing Case Study 1.mp4

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250 - Hypothesis Testing Calculations for Python.mp4

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251 - Hypothesis Testing Steps of Hypothesis Testing.mp4

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252 - Hypothesis Testing Code Outcomes.mp4

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253 - Hypothesis Testing Calculation of Z in Python.mp4

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254 - Hypothesis Testing Norm Function.mp4

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255 - Hypothesis Testing P Value Python.mp4

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256 - Correlation and Regression Module Introduction.mp4

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257 - Correlation and Regression Covariance and Correlation.mp4

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258 - Correlation and Regression Correlation.mp4

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259 - Correlation and Regression Regression.mp4

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260 - Correlation and Regression Correlation and Covariance in Python.mp4

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261 - Correlation and Regression Entering Input.mp4

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262 - Correlation and Regression Linear Regression Results.mp4

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263 - Multiple Regression Module Overview.mp4

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264 - Multiple Regression Motivation for Multiple Regression.mp4

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265 - Multiple Regression Formula for MR.mp4

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266 - Multiple Regression Preparing the Data.mp4

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267 - Multiple Regression Multiple Regression in Python.mp4

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Description

Python Mastery for Data Science & Statistical Modeling: Basics to Advanced Applications in Data Analysis, Visualization

What You'll Learn?

Solid grasp of Python programming for Data Science & Statistics
Practical experience through hands-on projects and case studies
Ability to apply Statistical Modeling techniques using Python
Understanding of real-world applications in Data Analysis and Machine Learning

Who is this for?

Beginners in Python and Data Science

Python Enthusiasts looking to apply skills in Data Analysis

Aspiring Data Scientists seeking a strong foundation

Professionals aiming to enhance their statistical modeling skills

What You Need to Know?

No prior knowledge or experience is required. Everything is explained from absolute basics.

More details

Description
Unlock the world of data science and statistical modeling with our comprehensive course, Python for Data Science & Statistical Modeling.
Whether you're a novice or looking to enhance your skills, this course provides a structured pathway to mastering Python for data science and delving into the fascinating world of statistical modeling.
Module 1: Python Fundamentals for Data Science
Dive into the foundations of Python for data science, where you'll learn the essentials that form the basis of your data journey.
Session 1: Introduction to Python & Data Science
Session 2: Python Syntax & Control Flow
Session 3: Data Structures in Python
Session 4: Introduction to Numpy & Pandas for Data Manipulation
Module 2: Data Science Essentials with Python
Explore the core components of data science using Python, including exploratory data analysis, visualization, and machine learning.
Session 5: Exploratory Data Analysis with Pandas & Numpy
Session 6: Data Visualization with Matplotlib, Seaborn & Bokeh
Session 7: Introduction to Scikit-Learn for Machine Learning in Python
Module 3: Mastering Probability, Statistics & Machine Learning
Gain in-depth knowledge of probability, statistics, and their seamless integration with Python's powerful machine learning capabilities.
Session 8: Difference between Probability and Statistics
Session 9: Set Theory and Probability Models
Session 10: Random Variables and Distributions
Session 11: Expectation, Variance, and Moments
Module 4: Practical Statistical Modeling with Python
Apply your understanding of probability and statistics to build statistical models and explore their real-world applications.
Session 12: Probability and Statistical Modeling in Python
Session 13: Estimation Techniques & Maximum Likelihood Estimate
Session 14: Logistic Regression and KL-Divergence
Session 15: Connecting Probability, Statistics & Machine Learning in Python
Module 5: Statistical Modeling Made Easy
Simplify statistical modeling with Python, covering summary statistics, hypothesis testing, correlation, and more.
Session 16: Overview of Summary Statistics in Python
Session 17: Introduction to Hypothesis Testing
Session 18: Null and Alternate Hypothesis with Python
Session 19: Correlation and Covariance in Python
Module 6: Implementing Statistical Models
Delve deeper into implementing statistical models with Python, including linear regression, multiple regression, and custom models.
Session 20: Linear Regression and Coefficients
Session 21: Testing for Correlation in Python
Session 22: Multiple Regression and F-Test
Session 23: Building Custom Statistical Models with Python Algorithms
Module 7: Capstone Projects & Real-World Applications
Put your skills to the test with hands-on projects, case studies, and real-world applications.
Session 24: Mini-projects integrating Python, Data Science & Statistics
Session 25: Case Study 1: Real-world applications of Statistical Models
Session 26: Case Study 2: Python-based Data Analysis & Visualization
Module 8: Conclusion & Next Steps
Wrap up your journey with a recap of key concepts and guidance on advancing your data science career.
Session 27: Recap & Summary of Key Concepts
Session 28: Continuing Your Learning Path in Data Science & Python
Join us on this transformative learning adventure, where you'll gain the skills and knowledge to excel in data science, statistical modeling, and Python. Enroll now and embark on your path to data-driven success!

Who Should Take This Course?
Aspiring Data Scientists
Data Analysts
Business Analysts
Students pursuing a career in data-related fields
Anyone interested in harnessing Python for data insights
Why This Course?
In today's data-driven world, proficiency in Python and statistical modeling is a highly sought-after skillset. This course empowers you with the knowledge and practical experience needed to excel in data analysis, visualization, and modeling using Python. Whether you're aiming to kickstart your career, enhance your current role, or simply explore the world of data, this course provides the foundation you need.Â

What You Will Learn:
This course is structured to take you from Python fundamentals to advanced statistical modeling, equipping you with the skills to:
Master Python syntax and data structures for effective data manipulation
Explore exploratory data analysis techniques using Pandas and Numpy
Create compelling data visualizations using Matplotlib, Seaborn, and Bokeh
Dive into Scikit-Learn for machine learning in Python
Understand key concepts in probability and statistics
Apply statistical modeling techniques in real-world scenarios
Build custom statistical models using Python algorithms
Perform hypothesis testing and correlation analysis
Implement linear and multiple regression models
Work on hands-on projects and real-world case studies

Keywords:
Python for Data Science, Statistical Modeling, Data Analysis, Data Visualization, Machine Learning, Pandas, Numpy, Matplotlib, Seaborn, Bokeh, Scikit-Learn, Probability, Statistics, Hypothesis Testing, Regression Analysis, Data Insights, Python Syntax, Data Manipulation
Who this course is for:
Beginners in Python and Data Science
Python Enthusiasts looking to apply skills in Data Analysis
Aspiring Data Scientists seeking a strong foundation
Professionals aiming to enhance their statistical modeling skills

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We are a group of experts, PhDs and Practitioners of Artificial Intelligence, Computer Science, Machine Learning, and Statistics. Some of us work in big companies like Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.We decided to produce a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of Machine Learning, Statistics, Artificial Intelligence, and Data Science. Initially, our objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory and without a long reading. Today we also publish a more complete course on some topics for a wider audience.Our courses have had phenomenal success. Our Courses have helped more than 100,000 students to master AI and Data Science.

AI Sciences Team

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