1. Business Analytics Using Excel.

Course Outline:

1. Data analytics cleaning and preparation
2. Descriptive statistics
3. Data analytics visualization techniques
4. Financial analysis

2. SQL Fundamentals

Course Structure:
1. Introduction to SQL
2. Data analytics types and operators
3. Database design
4. SQL queries (SELECT, INSERT, UPDATE, DELETE)
5. Advanced SQL concepts (joins, subqueries, window functions

3. Programming and Data Analytic with Python

Course Modules:
1. Python programming
2. Data analytics manipulation and data cleaning with Pandas
3. Statistical analysis with Python
4. Machine learning concepts and algorithm
5. Data analytics visualization with Matplotlib and Seaborn Module

4. Data Science with R Programming

Course Framework:
1. R programming
2. Data analytics manipulation and cleaning
3. Statistical analysis with R programming
4. Machine learning concepts and algorithms using python
5. Data analytics visualization with ggplot2

5. Tableau for Data Visualization

Program Outline:
1. Tableau basics and Tableau interface
2. Data sources and connection
3. Data modeling and transformation
4. Creating visualizations and dashboard
5. Sharing and collaborating on report

Power BI Training

Course Curriculum:
1. Power BI basics and interfacea
2. Data sources and connection
3. Data modeling and transformations
4. DAX Functions
5. Creating visualizations and dashboard in Power BI
6. Sharing and collaborating on report

AWS EC2

Course content
1. Lauch EC2
2. Lauch a website through girhub
3. Understanding Traffic
4. Understanding Load Balancer

Mongodb

1. Installation
2. DataBase
3. Collection
4. Query
5. Aggregate function