Course on
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
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
Batch | Time | Course Fee | |
---|---|---|---|
Open (One – One) | Flexible | INR 68000 USD 920 | |
Open (One – Batch) | Flexible | Contact us | 9841557655 |
Prerequisite : None
Curriculum
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
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









