End to End Data Visualization 2020-04-07T07:17:51+00:00

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End to End Data Visualization

Conveying the results of data analysis is much easier when the results are visualized using graphs, charts and other graphical formats. Python is an easy to learn, powerful programming language for data analysis. This course covers python packages such Matplotlib, Seaborn and other visual representations of data using Python. The course also covers two powerful Data Visualizations tools- Tableau and PowerBI, which enables analysts and business decision-makers to more easily visualize and communicate trends and patterns to stake holders to aid in effective decision making 

Video-Course Description

Key Features

  • Gain experience with handson exercises

  • Instructor led training

  • Flexibility of learning in class or online

  • Industry exposure – Use Cases

  • Learn by doing – Assignments, Tasks

  • Curriculum – par with Industry

  • Innovative Approach – Discussions, Quiz, webinar

  • Project Based Learning Approach

  • Capstone Projects

  • Solutions for your skill gaps

  • Upskilling and Level Setting

  • Dedicating mentoring sessions from industry experts

  • Career Support

  • Industry valued Certificate

Schedule – Online Instructor Led Training

BatchTimeCourse Fee
(One – One)
FlexibleINR 68000

USD 920

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(One – Batch)
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Prerequisite : None


The Origins of Python, Starting with Python: The Interactive Shell, Executing a Script, Indentation, Data Types and Variables, Operators, , Data Structures: Lists and Strings,, Sets and Frozen Sets, Tuples, Dictionaries, List Comprehension, Conditional Statements, Loops, while Loop, For Loops, Output with Print, Formatted output

Functions, Recursion and Recursive Functions, Parameter Passing in Functions,,Namespaces, Global and Local Variables, Decorators, Read and Write Files, Modular Programming and Modules, Packages in Python,Regular Expressions, Lambda Operator, Filter, Reduce and Map, List Comprehension, Iterators and Generators, Exception Handling, Tests, DocTests, UnitTests

Object Oriented Programming, Class and Instance Attributes, Properties vs. getters and setters, Inheritance, Multiple Inheritance, Magic Methods and Operator Overloading, Slots, Classes and Class Creation, Road to Metaclasses, Metaclass Use Case: Count Function Calls, Abstract Classes, Polymorphism

Numpy: Introduction, Numerical operations on Numpy, Pandas: Getting started with pandas, Data Frame Basics, Key Operations on Data Frames
Scatter Plot, Line Chart, Histogram, Bar Chart, Box plot, Heat Map, Pair plot, scatter Matrix using Matplotlib, Pandas Vizualization, Seaborn

Data Preparation, Creating visualization in Tableau, Tableau generated fields, Files in Tableau, Formatting Aggregation Filters Groups Sets, Loading text file with delimiters, Removing Report header, Ungroup the grouped data File with individual sheet names

Date functions in Tableau, Understanding Table Calculations, Addressing and Partitioning Table. FIXED, Include, Exclude & Nested LODs

Pareto chart, Waterfall chart, Market Basket Analysis, Moving/Rolling Average, Bump Chart, Sparkline, Clustering, Viz on Tooltip, Funnel chart, Parameters, Using Shapes and custom Shapes.

Custom Geocoding, Plotting points on background images, Using Mapbox, Using WMS Server, Connecting to Spatial data

Dash boarding and Story concepts, Integrating and creating visuals using R and Python

Connecting to a data Sources, Clean and Transform data with Query Editor, Combining Data – Merging and Appending, Views and Modelling Data, Cross Filter Direction, Create calculated tables and measures, Essential concepts in DAX, Data Types in DAX, DAX Functions, Measures in DAX, DAX tables and filtering. DAX queries and Parameter Naming

Charts in Power BI, Matrixes and tables, Slicers, Map Visualizations, Gauges and Single Number Cards, Shapes, text boxes, and images, Page layout and formatting, Z-Order, Dashboard vs. Reports, Quick Insights, Creating and Configuring Dashboards, Ask questions of data with natural language, Power BI embedded

Exploring live connections to data, Connecting directly to SQL Azure, HD Spark, SQL Server Analysis Services/ My SQL, Development API, Import Power View and Power Pivot to Power BI, Power BI Publisher for Excel, Content packs, Power BI Mobile, Report Server Basics, Web Portal, Paginated Reports, Data Gateways, Resources (Rest API/ SOAP API’s/ URL Access)

R Integration in Power BI Desktop, R visuals in Power BI, R Visuals in Power BI Service, Creating visual using Python

Capstone Project- I

Capstone Project- II

Tools Covered

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