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Data Analysis Diploma

Data Analysis Diploma

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5,000 EGP
Duration 20 Weeks
Total Hours 150 Hours
Projects 7 Projects
Certificate Verified

Course Overview

This Data Analysis Diploma provides comprehensive training in collecting, cleaning, analyzing, and visualizing data. Participants learn Excel, Power Query, Power Pivot, Python, SQL, Power BI, and Tableau, with practical projects to build real-world dashboards and reports. The course equips learners with the skills needed to make data-driven decisions and succeed as professional data analysts.

Course Syllabus

01 Module 1: Introduction & Excel for Data Analysis
  • What is Data Analysis
  • Types of Data
  • Data Lifecycle
  • Working with Excel Sheets & Data Tables
  • Using Formulas & Functions
  • Creating Advanced Formulas
  • Data Pipelines
  • Overview of Popular Data Analysis Tools
  • Designing Data-Driven Projects
  • Pivot Tables & Pivot Charts
  • Building Interactive Excel Dashboards
  • Connecting Excel to External Data Sources
02 Module 2: Power Query & Power Pivot
  • Introduction to Power Query
  • Importing Data from Multiple Sources
  • Data Cleaning & Transformation Techniques
  • Working with Folders and Batch Files
  • Creating Relationships Between Tables
  • Introduction to DAX
  • M Language Basics
03 Module 3: Applied Statistics for Data Analysts
  • Introduction to Statistics
  • Descriptive vs Inferential Statistics
  • Probability
  • Hypothesis Testing (T-Test
  • ANOVA)
  • Common Statistical Biases
04 Module 4: Data Visualization
  • Introduction to data analysis tools
  • Choosing the Right Graph
  • Power BI vs Tableau
  • Building Interactive Reports & Dashboards
  • Connecting to Excel
  • SQL & APIs
  • Using DAX for Advanced Calculations
  • Storytelling with Data & Report Design
05 Module 5: Python for Data Analysis
  • Introduction to Python & Jupyter Notebook
  • Python Basics (Variables
  • Loops
  • Conditions)
  • Data Handling & Cleaning
  • Data Collection Techniques
  • Web Scraping & Tools
  • Working with CSV
  • Excel
  • JSON
  • NumPy
  • Pandas
  • Matplotlib & Seaborn
06 Module 6: Databases & SQL
  • Introduction to Databases
  • Database Concepts & Table Relationships
  • SQL Essentials: SELECT
  • INSERT
  • UPDATE
  • DELETE
  • JOINS
  • GROUP BY & Aggregate Functions
  • Subqueries
  • Views
  • Stored Procedures
  • Ordering & Sorting Data
  • Connecting Python to SQL Databases
  • SQL for Data Analysis
07 Module 7: Real-World Projects & Applications
  • Excel Dashboards
  • Power BI Reports
  • Python & SQL Data Analysis Projects
  • Connecting Data Sources
  • Practical Hands-On Exercises