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Week 1 20
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IntroductionLecture1.1
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Getting Started With Anaconda DistributionLecture1.2
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Introduction to JupiterLecture1.3
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Pandas IntroductionLecture1.4
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Project on PandasLecture1.5
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Pivot Tables in PandasLecture1.6
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Cross Tables in PandasLecture1.7
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Comparison between Pivot and Cross tablesLecture1.8
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Seaborn Project IntroductionLecture1.9
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Seaborn IntroductionLecture1.10
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Get Started with the DataLecture1.11
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Introduction to Univariate PlotsLecture1.12
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Univariate Plots Practical ExerciseLecture1.13
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Introduction to Bivariate PlotsLecture1.14
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Multi Variate Plots in SeabornLecture1.15
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Regression Plots In SeabornLecture1.16
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Categorical Plots in SeabornLecture1.17
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Seaborn ProjectLecture1.18
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Facet Grids in SeabornLecture1.19
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Facet Grids Practical ExerciseLecture1.20
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Week 2 1
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Major Project : ObjectivesLecture2.1
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Week 3 17
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Project IntroductionLecture3.1
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Loading DataLecture3.2
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Exploring the DataLecture3.3
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Cleaning the DataLecture3.4
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Correlation and Frequency AnalysisLecture3.5
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Data Analysis with Group By MethodLecture3.6
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Data Analysis and Visualization with Pivot TableLecture3.7
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ata Analysis & Visualization with Cross TableLecture3.8
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Project FinalizationLecture3.9
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Plotly IntroductionLecture3.10
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Plotly Project: World Development IndicatorsLecture3.11
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Install and Load Plotly and DataLecture3.12
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Pie Charts In PlotlyLecture3.13
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Bar and Scatter in PlotlyLecture3.14
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Animation Plots in PlotlyLecture3.15
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Choropleth in PlotlyLecture3.16
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Plotly Project Wrap UpLecture3.17
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Week 4 6
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Functional Block BuildingLecture4.1
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GUI integration with Inputs and OutputsLecture4.2
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Accessing Data from Files with GUILecture4.3
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Use Case of Inventory Handling SoftwareLecture4.4
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Rules and Contingency Followed in DevelopmentLecture4.5
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User Friendliness and AccessibilityLecture4.6
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Getting Started With Anaconda Distribution
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