Data Analytics with R, Python and SQL

Analyze and Visualize the data

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Data Analytics with R, Python and SQL

What You Will Learn!

  • Develop data analysis methods, approaches and handling business problems using data analysis as a toolset
  • Uses R, Python, and SQL languages to implement the required statistical and mathematical methods to analyze practical datasets that are similar to the ones used
  • Gain insights, trends, patterns, and predict future course based on the historical data and present the findings
  • Work on a project that involves solving a business problem from start to finish; achieve end-to-end solution for the problem

Description

This course focusses on data analytic methods and approaches for getting business solutions using R and Python and SQL. Link business needs to data analytics. The course views data analytics as a set of tools to bringing business questions and problems addressed. High level goals of the course include:

Provide coding examples to look at the data from multiple perspectives

Learn the technologies for analyzing any dataset and to derive information

Learn on how to get the stories from the data and support business in potential opportunities

Learn key areas of analysis for any data and make meaningful insights into the data


At the end of course students will be able to do:

Code in R and Python for any dataset

Dig into the data to derive useful information

Handle problems from real world in both research and business areas

Gather smaller chunks of information from each analysis step

Prepare next set of steps to dig deeper into the data for additional information

Visualize data and present to audience for providing at each step of a data analytics project

Update and address related problems during and after the project is done and as data changes

Iterate the steps to achieve greater visibility and verify and validate the information before publishing


Who Should Attend!

  • Intended for beginners and intermediate learners/professionals who want to get into data analytics field and to accelerate their journey

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Subscribers

6

Lectures

33

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