Duration: 12h32m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 5.42 GB
Genre: eLearning | Language: English
Learn the data analysis and visualizations using R and Excel. Data manipulation using SQL in Oracle / MYSQL [2021]
What you'll learn
R programming from Beginning to Advance
Data Visualizations using ggDescription and Base Description
Learn to Description 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 Descriptions 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
Passion for Data
Description
The course is packed with real life projects examples
Get Transformed from Beginner to Expert .
Become expert in R programming.
Start using SQL queries in Oracle , MySQL
Start doing the extrapolatory data analysis ( EDA) on any kind of data and start making the meaningful business decisions.
Start writing simple to the most advanced SQL queries.
Integrate R and Python with Database and execute SQL command on them for data analysis and Visualizations.
Start making visualizations charts - bar chart , box Descriptions which will give the meaningful insights
Learn the art of Data Analysis , Visualizations for Data Science Projects
Learn to play with SQL on R and Python Console.
Integrate RDBMS database with R and Python
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)
Who this course is for:
Beginners who are looking to start career in Data Engineering and Data Science
Homepage
https://www.udemy.com/course/complete-data-analysis-course-for-absolute-beginners-2020/
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