Complete Data Analysis Course for Absolute Beginners [2020]

Complete Data Analysis Course for Absolute Beginners [2020]

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Complete Data Analysis Course for Absolute Beginners [2020] Learn the data analysis and visualizations using R and Excel. Data manipulation using SQL in Oracle / MySQL .

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What you'll learn

• R programming from Beginning to Advance
• Data Visualizations using ggplot and Base plot
• Learn to plot scatter , bar chart , histograms, time-series
• Upload real world data like bank marketing data with 45,000 records
• Start writing simple to the most advanced SQL queries in Oracle and MySQL
• Start using SQL queries on powerful R and Python console and plots graph for visualizations and data analysis
• Create own database in your laptop - Oracle and MySQL
• Import / Export files from and to database
• Acquisition Analytics to find out which customer segment is the profitable using EXCEL
• Investment Case Study to identify the top3 countries and investment type to help the Asset Management Company to understand the global trends using EXCEL

Requirements

1. Passion for Data

Description

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The course is packed with real life projects examples

1. Get Transformed from Beginner to Expert .
2. Become expert in R programming.
3. Start using SQL queries in Oracle , MySQL
4. Start doing the extrapolatory data analysis ( EDA) on any kind of data and start making the meaningful business decisions.
5. Start writing simple to the most advanced SQL queries.
6. Integrate R and Python with Database and execute SQL command on them for data analysis and Visualizations.
7. Start making visualizations charts - bar chart , box plots which will give the meaningful insights
8. Learn the art of Data Analysis , Visualizations for Data Science Projects
9. Learn to play with SQL on R and Python Console.
10. Integrate RDBMS database with R and Python
11. Create own database in your laptop/Desktop - Oracle and MySQL

Import and export data from and to external files.

Real world Case Studies Include the analysis from the following datasets

1. Bank Marketing datasets ( R )

2. Identify which customers are eligible for credit card issuance ( R)

3. Root Cause Analysis of Uber Demand Supply Gap ( R)

4. Investment Case Studies: To identify the top 3 countries and investment type to help the Asset Management Company to understand the global trends ( EXCEL)

5.  Acquisition Analytics on the Telemarketing datasets : Find out which customers are most likely to buy future bank    products using tele-channel. ( EXCEL) )

6. Market fact data.( SQL)