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Course Overview
Schedule of Classes
Course Curriculum
5 Subjects
Data Analysis and Visualization
211 Learning Materials
Resources
Dates and Times
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Regular Expressions
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Intro to Numpy
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Intro to Pandas
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Grouping Operations
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Filtering Operations
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Basics of Visualization
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Advanced Visualizations
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Animated Visualizations
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Interactive Visualizations
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Miscellaneous Charts
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SuperStore
Audio
Tableau Functions Workbook
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Dates and Times
Introduction to datetime
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The date and time class
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The datetime class
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The timedelta class
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Quiz on Dates and Times
Quiz Solution on Dates and Times
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Exercise on Date and Time
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Solution on Date and Time
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Regular Expressions
Meta Characters for Regular Expressions
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Built-in Functions for Regular Expressions
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Special Characters for Regular Expressions
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Sets for Regular Expressions
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Quiz on Regular Expressions
Quiz Solution on Regular Expressions
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Exercise on Regular Expressions
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Solution on Regular Expressions
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Introduction to Numpy
Array Creation using Numpy
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Mathematical Operations using Numpy
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Built-in Functions in Numpy
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Quiz on Introduction to Numpy
Quiz Solution on Introduction to Numpy
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Exercise on Built-in Functions in Numpy
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Exercise on Mathematical Operations using Numpy
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Solution on Mathematical Operations using Numpy
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Introduction to Pandas
Reading Datasets using Pandas
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Plotting Data in Pandas
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Indexing, Selecting, and Filtering Data using Pandas
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Merging and Concatenating DataFrames
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Lambda, Map, and Apply Functions
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Quiz on Introduction to Pandas
Quiz Solution on Introduction to Pandas
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Exercise on Pandas Plotting
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Solution on Pandas Plotting
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Exercise on Indexing and Selecting
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Solution on Indexing and Selecting
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Exercise on Merging and Concatenating
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Solution on Merging and Concatenating
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Exercise on Apply Functions
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Solution on Apply Functions
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Introduction to Data Exploration
How EDA can be useful
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Data Profiling
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Analyzing Target Data
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Quiz on Introduction to EDA
Quiz Solution on Introduction to EDA
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Examining Data
Summarizing the Data
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Exploring the Dabl Library
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Exploring the Sweetviz Library
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Using Color Gradients for better analysis
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Best Practices for Data Exploration
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Quiz on Examining Data
Quiz Solution on Examining Data
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Grouping Operations
Aggregate functions used for Grouping
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Using Groupby for Grouping Operations
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Groupby with Idxmax and Idxmin functions
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Using Color scales for better visualization
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Visualizing the Groupby Operations
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Using Pivot Tables for Grouping Operations
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Difference between Groupby and Pivot tables
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Performing Cross Tabulation
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Visualizing Cross tabulated Data
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Interactive Grouping Operations
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Quiz on Grouping Operations
Quiz Solution on Grouping Operations
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Filtering Operations
When to perform Filtering Operations
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Introduction to Simple Filtering Operations
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Advanced Filtering Operations
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Filtering and Grouping Operations
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Interactive Filtering Operations
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Quiz on Filtering Operations
Quiz Solution on Filtering Operations
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Basics of Visualization
Univariate Analysis
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Bivariate Analysis
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Multivariate Analysis
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Quiz on Basics of Visualization
Quiz Solution on Basics of Visualization
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Advanced Visualizations
Scatter Plots
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Charts with Colorscale
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Bar, Line, and Area Charts
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Facet Grids
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Statistical Charts
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Polar Charts
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Subplots
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3D Charts
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Waffle Charts
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Maps
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Quiz on Advanced Visualizations
Quiz Solution on Advanced Visualizations
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Animated Visualizations
Animation with Bubbleplot
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Animation with Facets
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Animation with Scatter Maps
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Animation with Choropleth Maps
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Quiz on Animated Visualizations
Quiz Solution on Animated Visualizations
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Interactive Visualizations
Introduction to Ipywidgets
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Interactive Univariate Analysis
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Interactive Bivariate Analysis
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Interactive Multivariate Analysis
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Quiz on Interactive Visualizations
Quiz Solution on Interactive Visualizations
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Miscellaneous Charts
Sunburst Charts
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Parallel Co-ordinate Charts
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Funnel Charts
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Gantt Charts
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Ternary Charts
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Tree Maps
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Network Charts
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Quiz on Miscellaneous Charts
Quiz Solution on Miscellaneous Charts
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Tableau Functions
Section Overview
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Getting Started with Calculations
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Types of Calculations
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The Number Functions
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The String Functions
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Searching for Text
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Type Conversions
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The Date Functions
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Datetrunc and datepart
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Gantt Charts using Date Functions
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The Logical Functions
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Calculations using Sets
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Aggregate Functions
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Attribute Function
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Quiz on Tableau Functions
Table Calculations
Section Overview
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Table Calculation - Part 1
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Table Calculations - Part 2
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Table Functions
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Window Functions
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Conditional Highlighting using Windows Functions
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Moving Calculations
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Rank Functions
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Running Functions
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Secondary Calculations with Pareto Chart
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Level of Detail (LOD) Expression
Resources - Global Superstore
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Resources LOD Workbook
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Introduction to Level of Details
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FIXED - Level of Detail Expression
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Customer Order Loyalty
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Customer Retention Analysis
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Removing Duplicate Records in Tableau using FIXED
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INCLUDE - Level of Detail Expression
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EXCLUDE - Level of Detail Expression
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Table Scoped Level of Detail Expression
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Nested LOD
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Finding a Dimension at Lower Level
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Sparklines with Min Max Indicator
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Final Words
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Parameters in Tableau
Resources SuperStore
Audio
Resources Parameters Workbook
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Parameters
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Parameter Basics
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Advanced Parameters Part - 1
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Advanced Parameters Part - 2
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Quiz on Parameters in Tableau
Introduction to Data Preparations
Resources Data Preparation Datasets
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Resources Data Preparation Workbooks
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Managing Metadata and Data Types
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Data Extraction
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Data Preparation and Cleaning
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Wide and Long Formats
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Filtering of Rows using Data Source Filters
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Joins
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Joining Multiple Fields
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Complex Joins
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Why Blending?
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How to do Blending in Tableau?
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Data Blending (Additional)
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Data Union
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Quiz on Data Preparations
Slicing & Dicing Data in Tableau
Resources Slicing & Dicing Datasets
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Resources Slicing & Dicing Workbook
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Sorting
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Hierarchy
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Groups
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Sets
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Data Filters
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Advanced Filtering
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Quiz on Slicing and Dicing Data in Tableau
Tableau Maps
Resources Superstore_dataset
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Resources Tableau Maps Workbook
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Beginner Guide to maps
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Background Maps & Layers
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Dual Axis Map
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Geocoded Fields
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Working with Web Map Service (WMS)
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Custom Background Images
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Quiz on Tableau Maps
Dashboards
Resources shark-data-cleaned
Audio
Resources Dashboards Workbook
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Section Overview
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The Storytelling
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Building Blocks of Dashboard - Part 1
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Building Blocks of Dashboard - Part 2
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Building Blocks of Dashboard - Part 3
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Dashboard
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Containers
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Dashboard Actions
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Quiz on Dashboards
Data Cleaning and Preparation
92 Learning Materials
Resources
Data Cleaning
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Feature Engineering
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Data Pre-Processing
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Dimensionality Reduction
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Missing Values Treatment
Causes and Impact of Missing Values
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Types of Missing Values
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When should we delete the missing values
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Imputing missing values with the business logic
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Imputing missing values with Mean/Median/Mode
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Imputing missing values in a real-time scenario
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Quiz on Missing Values Treatment
Quiz Solution on Missing Values Treatment
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Outliers Treatment
How outliers can be harmful for machine learning models
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Finding out outliers from the data
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Using Winsorization to deal with outliers
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Deleting and Capping the outliers
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Dealing with outliers in a real-world scenario
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Quiz on Outliers Treatment
Quiz Solution on Outliers Treatment
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Data Manipulation Functions
Introduction to reindex, set_index, reset_index, and sort_index Functions
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Introduction to Replace and Droplevel Function
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Introduction to Split and Strip Function
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Introduction to Stack, and Unstack Functions
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Introduction to Melt, Explode, and Squeeze Functions
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Data Cleaning on Real World Datasets
Data Cleaning on Big Mart Dataset
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Data Cleaning on Movie Dataset
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Data Cleaning on Melbourne Housing Dataset
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Data Cleaning on Naukri Dataset
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Introduction to Feature Engineering
Introduction to Feature Engineering
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Removing Unnecessary Columns
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Decomposing Time and Date Features
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Decomposing Categorical Features
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Binning Numerical Features
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Aggregating features
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Quiz on Feature Engineering
Quiz Solution on Feature Engineering
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Feature Engineering on the Text Data
Introduction to Feature Engineering on Text Data
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Reading and Summarizing the Text Data
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Finding the Length, Polarity and Subjectivity
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Finding the Words, Characters, and Punctuation Count
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Counting Nouns and Verbs in the Text
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Counting Adjectives, Adverb, and Pronouns
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Quiz on Feature Engineering on the Text Data
Quiz Solution on Feature Engineering on the Text Data
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Feature Engineering Functions
Introduction to Assign and Update Functions
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Introduction to at_time and between_time Functions
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Introduction to nlargest and nsmallest Functions
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Introduction to Expanding Function
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Introduction to Cumulative Functions
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Feature Engineering on Real World Datasets
Feature Engineering on Employee Data
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Feature Engineering on FIFA Data
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Feature Engineering on Hotel Reviews
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Feature Engineering on Marketing Data
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Feature Engineering on Titanic Data
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Dealing with Categorical data
Types of Encoding Techniques
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Label Encoding
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Feature Mapping for Ordinal Variables
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OneHot Encoding
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Binary and BaseN Encoding
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Mean and Frequency Encoding
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Quiz on Dealing with Categorical data
Quiz Solution on Dealing with Categorical data
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Data Transformation
Introduction to Skewness and Normal Distribution
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Square and Cube Root Transformation
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Log transformation
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Box Cox transformation
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Quiz on Data Transformation
Quiz Solution on Data Transformation
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Data Splitting and Feature Scaling
Train,Test and Validation Split
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Standardization and Normalization
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Quiz on Data Splitting and Feature Scaling
Quiz Solution on Data Splitting and Feature Scaling
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Introduction to Dimensionality Reduction
Why High Dimensional Datasets are a Problem
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Methods to solve the problem of High Dimensionality
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Solving a Real World Problem
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Quiz on Introduction
Correlation Filtering
Introduction to Correlation using Heatmap
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Removing Highly Correlated Columns using Correlation
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Quiz on Correlation Filtering
Feature Selection
Introduction to Recursive Feature Selection
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Implementing Recursive Feature Selection
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Implementing the Boruta Algorithm
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Implementing the Boruta Algorithm
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Quiz on Feature Selection
Machine Learning
Introduction to Principal Component Analysis
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Implementing PCA
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Introduction to t-SNE
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Implementing t-SNE
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Introduction to Linear Discriminant Analysis
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Implementing LDA
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Difference between PCA, t-SNE, and LDA
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Quiz on Machine Learning
Introduction to ML
51 Learning Materials
Introduction to Machine Learning
How Industries are using Machine learning
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Supervised Vs Unsupervised Techniques
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Classification Vs Regression
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Quiz on Introduction to Machine Learning
Quiz Solution on Introduction to Machine Learning
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Modelling with Linear Regression
Introduction to Linear Regression
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Implementing Linear Regression using sklearn
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Feature Selection using RFECV
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Data Transformation with Linear Regression
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Applying Cross Validation
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Analyzing the performance of Regression models
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R2 score and adjusted R2 score intuition
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MAE, RMSE, R2 and Adjusted R2 in code
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Applying real time prediction on our model
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Industry relevance of linear regression
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Quiz on Modelling with Linear Regression
Quiz Solution on Modelling with Linear Regression
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Linear Regression – Materials
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Regularization Techniques
What is Regularizationa and why is it important?
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Getting the intuition of Lasso, Ridge and Elastic Net
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Understanding when to apply Lasso, Ridge and Elastic Net
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Applying Lasso, Ridge and Elastic Net in sklearn
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Quiz on Regularization Techniques
Resources - Regularization Techniques
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Quiz Solution on Regularization Techniques
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Modelling with Logistic Regression
Introduction to Logistic Regression
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Implementing Logistic Regression using sklearn
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Feature selection using RFECV
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Hyperparameter tuning using Grid search
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Applying Cross validation
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How to analyze performance of a classification model
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Using accuracy score to analyze the performance of model
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Using ROC-AUC score to analyze the performance of model
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Introduction to Clustering Analysis
Resources
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Introduction to Clustering
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Types of Clustering
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Applications of Clustering
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Quiz on Introduction to Clustering
K Means Clustering
Using the Elbow method for choosing the best value of K
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Introduction to K-Means clustering
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Solving a Real World Problem
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Implementing K Means on the Mall Dataset
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Using Silhouette Score to analyze the clusters
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Clustering Multiple Dimensions
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Quiz on K Means Clustering
Advanced Clustering Techniques
Introduction to Hierarchal Clustering
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Introduction to Dendrograms
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Implementing Hierarchical Clustering
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Introduction to DBSCAN Clustering
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Implementing DBSCAN Clustering
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Quiz on Advanced Clustering Techniques
Tableau & Data Visualization Bootcamp
43 Learning Materials
Creating your First Tableau Dashboard
Getting Started with Tableau
External Link
Navigating Tableau
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Creating Your First Visualization
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Building Your First Dashboard
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Building Blocks of Data Visualization
Introduction
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Dimensions and Measures
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Green & Blue Pills
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Measures Names & Values
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Working with Time Series Data
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Aggregation and Granularity
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Aggregation Options
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Show Me Toolbar
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Marks cards & Level of Detail
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Custom Shapes
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Filtering Data
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