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Data Analysts Toolbox: Excel, SQL, Python, Power BI, Tableau

سرفصل های دوره

Gain Real World Skills By Mastering Excel, SQL, Python, Power BI, and Tableau for Data Analysts


1. Introduction to Data Analysis
  • 1. Introduction
  • 2. Understanding the role of a data analyst.html
  • 3. Overview of data analysis tools and their importance.html
  • 4. Introduction to key concepts in data analysis.html

  • 2. Excel for Data Analysis
  • 1. Introduction to Excel for Data Analysis.html
  • 2. Basic to advanced Excel functions and formulas.html
  • 3. Hands-on Practice of Functions and Formulas
  • 4. Using Formulas for Arithmetic Tasks
  • 5. Re-using Formulas
  • 6. Calculating YTD Profits
  • 7. Calculating Percentage Change
  • 8. Relative and Absolute Reference
  • 9. Using RANK Function
  • 10. STD Function
  • 11. Small and Large Functions
  • 12. Median Functions
  • 13. COUNT and COUNTA Functions
  • 14. What is Power Query
  • 15.1 EV sales (King county).zip
  • 15. Connecting to a data source
  • 16. Please Read.html
  • 17.1 Prep.xlsx
  • 17. Preparing your query
  • 18.1 Cleansing.xlsx
  • 18. Cleansing data
  • 19.1 Enhance.xlsx
  • 19. Enhancing query
  • 20. What is Power Pivot
  • 21.1 PrepPP.xlsx
  • 21. Creating a data model
  • 22.1 AddData.xlsx
  • 22. Importing data and creating relationships
  • 23.1 Lookups.xlsx
  • 23. Create lookups with DAX
  • 24.1 Pivot.xlsx
  • 24. Analyze data with Pivot Tables
  • 25.1 Charts.xlsx
  • 25. Analyze data with Pivot Charts

  • 3. SQL Fundamentals
  • 1. Introduction to SQL and its applications in data analysis.html
  • 2. What is MySQL.html
  • 3. MySQL Installation (Windows)
  • 4. MySQL Installation (Mac)
  • 5. What is MySQL Workbench
  • 6. Installing MySQL Workbench ( Mac)
  • 7. Database Concepts
  • 8. What is a Schema
  • 9. What is a Database Schema
  • 10. MySQL Data Types
  • 11. Exploring Basic SQL Commands
  • 12. Showing existing databases
  • 13. Showing lists of tables
  • 14. Create a table
  • 15. Displaying table structure
  • 16. Changing table structure
  • 17. Creating MySQL Database
  • 18.1 table+create+script.zip
  • 18. Creating MySQL Table
  • 19. Setting a default database
  • 20. Primary Keys
  • 21. Foreign Keys
  • 22. SQL & MySQL SELECT Statement
  • 23.1 insert+data+into+tables.zip
  • 23. SQL & MySQL INSERT Statement
  • 24. SQL & MySQL UPDATE Statement
  • 25. SQL & MySQL DELETE Statement
  • 26. Introduction to Joins.html
  • 27. INNER JOIN
  • 28. LEFT JOIN
  • 29. RIGHT JOIN
  • 30. SELF JOIN
  • 31. What is sub query
  • 32. Nested sub query
  • 33. Filtering data with WHERE Clause
  • 34. Sorting data with ORDER BY Clause
  • 35. Grouping data with GROUP BY Clause
  • 36. What are aggregate functions
  • 37. AVG Aggregate Function
  • 38. COUNT Aggregate Function
  • 39. SUM Aggregate Function
  • 40. MIN Aggregate Function
  • 41. MAX Aggregate Function

  • 4. Data Analysis with Python and Jupyter Notebook
  • 1. What is Python.html
  • 2. Using Python in Data Analysis.html
  • 3. What is Jupyter Notebook.html
  • 4. Installing Jupyter Notebook Server
  • 5. Running Jupyter Notebook Server
  • 6. Jupyter Notebook Components
  • 7. Jupyter Notebook Dashboard
  • 8. Jupyter Notebook User Interface
  • 9. Creating a new notebook
  • 10. Kaggle Data Sets
  • 11.1 us_baby_names.zip
  • 11. Tabular Data
  • 12. what is Pandas DataFrame.html
  • 13. Exploring Pandas DataFrame
  • 14. Manipulating a Pandas DataFrame
  • 15. What is data cleaning
  • 16.1 crime_boston.zip
  • 16. Basic data cleaning process
  • 17.1 listings.zip
  • 17. What is data visualization
  • 18. Visualizing Qualitative Data
  • 19. Visualizing Quantitative Data

  • 5. Data Analysis with Power BI
  • 1. What is Power BI.html
  • 2. What is Power BI Desktop
  • 3. Installing Power BI Desktop
  • 4. Exploring Power BI Desktop
  • 5.1 Financial+Sample.xlsx
  • 5. Power BI Overview Part 1
  • 6. Power BI Overview Part 2
  • 7. Power BI Overview Part 3
  • 8. Components of Power BI
  • 9. Building Blocks of Power BI
  • 10. Explore Power BI Service
  • 11. Connect to web data
  • 12. Clean and transform data Part 1
  • 13. Clean and transform data Part 2
  • 14. Combining Data Sources
  • 15. Visualizing Data Part 1
  • 16. Visualizing Data Part 2
  • 17. Publishing Reports to Power BI Service

  • 6. Data Analysis with Tableau
  • 1. What is Tableau.html
  • 2. Using Tableau for Data Analysis.html
  • 3. Tableau Public Desktop
  • 4.1 World_Bank_CO2.xlsx
  • 4. Tableau Public Desktop Overview Part 1
  • 5. Tableau Public Desktop Overview Part 2
  • 6. Tableau Online
  • 7. Tableau Data Sources
  • 8.1 SampleData.xlsx
  • 8. Connecting to data source
  • 9.1 JoinExamples.xlsx
  • 9. Join related data sources
  • 10.1 DifferentNames.xlsx
  • 10. Join data sources with inconsistent fields
  • 11.1 CleanData.xlsx
  • 11. Data cleaning
  • 12. Tableau Interface
  • 13. Reordering Visualization
  • 14. Change summary
  • 15.1 split.zip
  • 15. Split text into multiple columns
  • 16.1 storylines.zip
  • 16. Presenting data using stories
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