Data Analytics with R, Python and SQL

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Free Download Data Analytics with R, Python and SQL
Published 1/2024
Created by Ramesh Babu Paramkusham
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 33 Lectures ( 6h 31m ) | Size: 3.3 GB

Analyze and Visualize the data
What you'll 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
Requirements:
Working knowledge of computers and software, and basic knowledge of math/statistics. Prior programming knowledge helps. Suitable for both technical and business professionals with interest to learn
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 includerovide coding examples to look at the data from multiple perspectivesLearn the technologies for analyzing any dataset and to derive informationLearn on how to get the stories from the data and support business in potential opportunitiesLearn 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 informationHandle problems from real world in both research and business areasGather smaller chunks of information from each analysis stepPrepare next set of steps to dig deeper into the data for additional informationVisualize data and present to audience for providing at each step of a data analytics projectUpdate and address related problems during and after the project is done and as data changesIterate the steps to achieve greater visibility and verify and validate the information before publishing
Who this course is for:
Intended for beginners and intermediate learners/professionals who want to get into data analytics field and to accelerate their journey
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