Data Science With Python Course Hands-On Data Science

سرفصل های دوره

1 - Introduction

1 - Download and Install Anaconda Windows

1 - anaconda linux installation.zip

1 - anaconda mac os installation.zip

1 - anaconda windows installation.zip

2 - Download and Install Anaconda Ubuntu Linux

3 - Overview Of Jupyter Notebook

3 - jupyter notebook documentation.zip

4 - Notes About Course

5 - Course FAQ.html

6 - Join Online Classroom.html

2 - Python crash course

7 - Introduction Python

7 - Python-Crash-Course.zip

8 - Python Number String Variable

9 - Python List tuples Dictionary Set

10 - Python Ifelse Looping

11 - Python Function Lambda Map

12 - Python Exercise.html

3 - Data analysis with Numpy

13 - Introduction Numpy Numerica Python

13 - Numpy.zip

14 - Numpy array

15 - Numpy array operations

16 - Indexing Slicing Numpy array

16 - visualize numpy.zip

17 - Numpy Exercise.html

4 - Data analysis with Pandas

18 - Introduction Pandas

18 - Pandas.zip

19 - Pandas Introduction to Series

20 - Pandas Introduction to Dataframe

21 - Dataframe Index Multiindex

22 - Handling Missing Data dropna fillna

23 - Grouping data

24 - Read Write csv html excel file

25 - Visualization of data with pandas

5 - Data Visulization with Matplotlib

26 - Introduction

26 - MatPlotLib.zip

27 - Why Visualization.html

28 - MatplotLib Basic plotting Plotting terminology

29 - MatplotLib Subplots

30 - Matplotlib Special plot

6 - Data visualization plotly

31 - Plotly introduction

31 - plotly.zip

32 - Basic plotting plotly

33 - Exercise Extend Basic Plot.html

34 - Plotly scatter and line chart

35 - Plotly Bar chart

36 - Exercise Extend Bar Chart.html

37 - Plotly Bubble chart

38 - Plotly Histogram and Distribution plot

7 - Data visualization with Tableau

39 - Introduction to Tableau and Installation

40 - Insight 1

40 - countries-of-the-world.csv

41 - Insight 2

42 - Load Data in Tableau

42 - countries-of-the-world.csv

43 - Save Tableau Worksheet

8 - Introduction to Data

44 - Introduction to Data Continuous and Discrete Data

45 - Nominal and Ordinal Data

9 - Importing Data in python

46 - Importing-Data.zip

46 - Introduction

47 - Reading Plain text file

47 - news.zip

48 - Reading csv file

48 - mnist.csv

48 - titanic.csv

49 - ExcelTest.xlsx

49 - MatlabTest.zip

49 - Reading Excel and m Matlab file

50 - Read Sqlite Database

50 - SqliteTestDb.zip

51 - Fetch Data from Remote file

52 - Fetch Data from Facebook API

10 - Data Preprocessing

53 - Data-Preprocesing.zip

53 - Introduction

54 - Data.csv

54 - Reading Data

55 - Handling Missing Data

56 - Categorical Data

57 - Splitting Data in Training and Testing Set

58 - Normalize Data

11 - Web Scraping

59 - Introduction Web Scraping

59 - Web-Scraping.zip

60 - What is Web Scraping

61 - Web Scraping Process

62 - Search Element by TagName and TagByClass

63 - How to use developer tools in browser

64 - Practical Activity.html

12 - Exploratory Data analysis

65 - EDA of pima indian diabetes dataset

66 - Visualize pima indian diabetes dataset

13 - Data transformation and Scaling Data

67 - Introduction

68 - Rescale data Standardize data

69 - Normalize Data Binarize Data

70 - Practical Activity.html

14 - Moving towards Machine Learning

71 - What is Machine Learning In Layman term

71 - towards-ML.zip

72 - Traditional system of computing vs Machine Learning

73 - Formal Definition of Machine Learning

74 - How Machine Learning system works

75 - Different Types of Machine Learning system Supervised vs Unsupervised learning

76 - Parametric vs Nonparametric machine learning system

77 - Machine Learning system design and Scikit learn

78 - Machine Learning application

79 - Ask yourself to learn any machine learning algorithm

15 - Feature selection for Machine Learning

80 - Introduction to feature selection

81 - Univariate feature selection

82 - Recursive feature elimination

83 - Principal component analysis

84 - Remove feature with low variance

85 - Tree based method for feature selection

16 - K nearest neighbour

86 - Section introduction

87 - KNN algorithm Intitution

88 - Choose K and distance metric

89 - About KNN algorithm

90 - Implement KNN from scratch.html

90 - KNN.zip

17 - Linear Regression

91 - Introduction

92 - Python Implementation Step 1

93 - Python Implementation Step 2

94 - Python Implementation Step 3

18 - Logistic Regression

95 - Introduction

96 - Python Implementation Step 1

97 - Python Implementation Step 2

19 - Big Data analysis with Apache Spark PySpark Python

98 - Introduction.html

99 - What is Apache Spark

100 - Introduction to Installation

101 - Installation Part 1 and 2

102 - Installation Part 3 and 4

103 - Installation Instruction Windows.html

104 - Spark Session

105 - Import JSON data into Dataframe

105 - student.zip

106 - What next.html

20 - Appendix

107 - Create Python virtual environment 1

108 - Create Python virtual environment 2

109 - Conda Command I

110 - Conda Command II

111 - Python Numbers & Math operators

112 - Python Variables and Datatypes

113 - Python Dynamic Typing in Python

114 - Python String

115 - Python Boolean variable and conditional logic

116 - Python Looping in Python

21 - Data Science in Cloud

117 - Data Science in Cloud 1

118 - Data Science in Cloud 2 Microsoft Azure

119 - Install tensorflow Keras and NLTK on Azure VM

22 - Data Science other field

120 - Data Science as Interdisciplinary field

121 - Statistics & Probability

122 - Mathematics

123 - Visualization

124 - Database and Computer Science

125 - Big data Technology

126 - Machine Learning

127 - Deep Learning

128 - Natural language Processing

23 - Prerequisite for Machine Learning and Data Science

129 - Welcome to Mathematics Prerequisite.html

24 - Probability

130 - Permutations

130 - Permutation-and-Combination.pptx

130 - Probability.pptx

131 - Permutations Exercise

132 - Combinations

133 - Introduction to Probability

134 - Union Intersection of complement of event

135 - Independent and dependent event

25 - Probability Puzzles

136 - Probability interview question 1.html

137 - Probability interview answer 1

138 - Probability interview question 2.html

139 - Probability interview answer 2

140 - Probability interview question 3.html

141 - Probability interview answer 3

142 - Probability interview question 4.html

143 - Probability interview answer 4

144 - Probability interview question 5.html

145 - Probability interview answer 5

26 - Statistics

146 - Measure of central tendency

147 - Mean vs Median

148 - Measure of Dispersion

149 - Quartiles and Interquartile range

150 - Correlation vs Causality

151 - Covariance and Pearson correlation

152 - Measure Statistical Parameter with Microsoft Excel

152 - Measure-Statistics-with-Excel.xlsx

27 - Bonus Special Offer

153 - Discount for other courses.html

45,900 تومان

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تولید کننده: Udemy-Training