Udemy - The Data Analyst's Toolkit - Excel, SQL, Python, Power BI torrent

The Data Analyst's Toolkit: Excel, SQL, Python, Power BI
https://FreeCourseWeb.com

Published 5/2023
Created by Digital Learning Academy
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 139 Lectures ( 12h 9m ) | Size: 3.53 GB

Data Mastery for the Modern Analyst: Excel, SQL, Python, and Power BI Techniques

What you'll learn
The roles and responsibilities of a data analyst
The importance of data-driven decision-making in organizations.
How to use Microsoft Excel for data manipulation and analysis.
Data cleaning and formatting techniques in Excel.
How to create and use pivot tables
Data visualization techniques using Excel charts.
Writing basic SQL queries for data retrieval from relational databases.
Advanced SQL techniques, such as filtering, sorting, aggregating, and joining multiple tables.
The basics of the Python programming language for data analysis.
How to use Python libraries like Pandas for data manipulation.
Data visualization techniques using Python libraries such as Matplotlib.
Connecting to data sources, data cleaning, and transformation in Power BI.
Creating interactive dashboards and reports using Power BI.

Requirements
Basic computer literacy: Students should be comfortable using computers and navigating various software applications, as well as have a general understanding of file management.
Familiarity with Microsoft Office Suite: A basic understanding of Microsoft Office applications, particularly Excel, will be helpful for students as they dive into more advanced data analysis techniques using Excel.
Problem-solving mindset: A curiosity for solving problems and a willingness to explore various approaches to data analysis will help students succeed in this course.
No prior programming experience is required, but a basic understanding of programming concepts and logic will be beneficial when learning Python and SQL.
Access to required software: Students should have access to a computer with Microsoft Excel, Power BI, and a Python development environment (e.g., Anaconda) installed. Access to a SQL database environment (e.g., MySQL, PostgreSQL, or SQL Server) is also recommended for practicing SQL queries.