Data Visualization Including Machine Learning Concepts using Tableau

Data Visualization Including Machine Learning concepts Online Training includes 30 hours of hands-on exposure to ensure that you are left will a feeling of being an expert at the Tableau tool usage. We have considered the industry requirement & devised the course to ensure that you have the practical exposure required to swim through the interviews with ease. The case studies explained towards the end will only reinforce the practice learning to make you complete to face the real world projects & problems which are solved using Tableau. The datasets chosen ensures that you learn every option completely. With a lot of industry connects you get to know the job opportunities which none would otherwise. This course will help you unlock new career opportunities and gain an edge over other analysts. Our course will help you understand architecture.

Introduction to Data Visualization with Tableau

What is Data Visualization?
Identify the prerequisites, goal, objectives, methodology, and Goal.
Architecture of Tableau

What is Tableau?
Features of Tableau.
Installation of Tableau Desktop.
The interface of Tableau(Layout/Toolbars/Data Pane/Analytics Pane etc).
Managing Data Sources

Connection to various data sources
Mysql Database connectivity and tables
ODBC and other sources connectivity
Introduction to Visual Analytics with Tableau.

Introduction to various charts
Bar Charts, Line Graphs, Pie Charts
Maps, Scatter Plots, Gantt Charts, Bubble Charts
Treemaps and Box-and-Whisker Plots
Deep dive into Visualization

Highlighting Tables, Heat Maps.
Circle Plots
Side By Sidebar charts, Dual Axis Charts, Area Charts.
Waterfall Charts, Bump Chart, Word Cloud Chart, Pareto Charts.
Multiple fields: continuous and discrete visualization
Data Organization and Scripting

Calculated Metrics, Apply Sorting on Dimension and Measures.
Calculating Total and Subtotals.
Various Aggregated measures, Percentages.
Data Spotlighting, Summary Card, Date and Time Functions.
Logical Functions.
Hierarchies, Groups, and Bins.
Prediction with extrapolation
Working with Time Dimension

Quick Table Calculations.
Custom Table Calculations,
YTD, Parallel Period, Moving Averages.
Running totals, Window Averages,
Trend Lines and Predictive Models
Data Incremental Loading and Data Blending

Data Blending from multiple source systems Creating Incremental Loads
Creating File Extractions, Parameters
Python: Environment Setup and Essentials

Python Environment Installation and Configuration.
Jupyter Notebook Installation
Jupyter Notebook Introduction
Variable Assignment
Basic Data Types: Integer, Float, String, None, and Boolean; Typecasting
Creating, accessing, and slicing tuples
Creating, accessing, and slicing lists
Creating, viewing, accessing, and modifying dicts
Creating and using operations on sets
Basic Operators: 'in', '+', '*'
Functions
Control Flow
Data Manipulation with Python (Pandas)

Introduction to Pandas
Data Structures
Series
DataFrame
Missing Values
Data Operations
Data Standardization
Pandas File Read and Write Support
SQL Operation
Machine Learning with Python (ScikitLearn)

Introduction to Machine Learning
Machine Learning Approach
How Supervised and Unsupervised Learning Models Work
Scikit-Learn
Supervised Learning Models - Linear Regression
K Nearest Neighbors (K-NN) Model
Unsupervised Learning Models: Clustering
Unsupervised Learning Models: Dimensionality Reduction
Model Persistence
Apply Machine learning concepts in Tableau

Linear Regression.
Clustering (K -Means)
Data Forecasting
Pearson correlation coefficient
Integrate Tableau with Python using Tabby server.
Tableau Server Comprehensive

Single Installer
Worker Installer
Authentication
Processes
Data Server
Create the First Admin User
Create Projects and Groups
Assign Permissions to Projects
Data Connections
Metadata management
Connecting to data with Data Server
Updating data sources