Data Analysis Diploma
96 Hours
A complete, hands-on path to becoming a professional data analyst
This diploma is designed to take you from data analysis fundamentals to building advanced dashboards, reports, and insights using the most in-demand tools
You will gain practical skills that enable you to analyze data, communicate insights, and support data-driven decision-making across industries
Why Data Analysis now
🚀 Every business depends on data to make informed decisions
🚀 Data analysts are among the most in-demand roles across all sectors
🚀 This diploma focuses on real tools, real projects, and real-world analysis skills
Core skills you will master
🐍 Analyze data using Python with real-world datasets
📊 Build advanced reports and dashboards using Power BI
📈 Perform data analysis and visualization using Excel at a professional level
🗄 Query, manipulate, and analyze data using SQL databases
📉 Communicate insights clearly through charts, dashboards, and storytelling
🏗 Apply data modeling, ETL, and best practices used in professional environments
Learning experience and deliverables
🎟 Ticket system for continuous instructor support
🛠 Multiple hands-on projects across Python, Excel, SQL, and Power BI
⏱ 96 intensive training hours focused on applied learning
📝 Assignments that reinforce technical and analytical skills
Quality, licensing, and recognition
🏛 Licensed by the Ministry of Communications and Information Technology
🏢 Registered member of the Information Technology Industry Development Agency ITIDA
📜 ISO 9001:2015 certified quality management system
🔧 Training programs accredited by the Egyptian Appliances Syndicate
👷 Training programs accredited by the Engineers Syndicate
⚙ Training programs accredited by the Applied Professions Syndicate
What you will study
📘 Core Data Analysis topics that provide learners with the technical knowledge and practical skills required for professional data analyst roles
Diploma curriculum
Introduction to Data Analysis
📌 Introduction to Data Analysis
📌 Data Analyst Role & Responsibilities
📌 Types of Data (Structured / Unstructured)
📌 Data Lifecycle
📌 Data-Driven Decision Making
📌 Tools Overview (Excel, Python, SQL, Power BI, Tableau)
Excel Basics & Excel for Data Analysis
📌 Excel Interface & Navigation
📌 Data Entry & Formatting
📌 Basic Formulas
📌 Functions (SUM, AVERAGE, IF, COUNT, VLOOKUP/XLOOKUP)
📌 Data Sorting & Filtering
📌 Data Validation
📌 Conditional Formatting
📌 Basic Charts
Data Visualization with Excel
📌 Chart Types (Bar, Line, Pie, Area, Scatter)
📌 Chart Design Principles
📌Data Storytelling with Charts
📌 Dashboard Basics
📌 Dynamic Charts
📌 Pivot Charts
📌 Visual Best Practices
Data Analysis with Python
📌 Variables & Data Types
📌 Conditions & Loops
📌 Functions
📌 Lists, Tuples, Dictionaries
📌 NumPy & Pandas DataFrames
📌 Data Importing (CSV, Excel, JSON)
📌 Data Cleaning & Handling Missing Values
📌 Data Transformation
📌 Data Filtering & Selection
📌 Data Merging & Joining
Data Visualization with Python
📌 Matplotlib
📌 Seaborn
📌 Plot Types
📌 Data Exploration
📌 Visual Analytics
📌 Storytelling with Data
📌 Interactive Visualization (Intro)
SQL for Data Analysis
📌 Databases Concepts
📌 Tables & Relationships
📌 SELECT Statements
📌 WHERE, ORDER BY, LIMIT
📌 Aggregations (COUNT, SUM, AVG, MAX, MIN)
📌 GROUP BY & HAVING
📌 JOINs (INNER, LEFT, RIGHT, FULL)
📌 Subqueries
📌 Views
📌 Indexes
📌 Data Cleaning with SQL
Statistics & Probability for Data
📌 Descriptive Stats
📌 Distributions
📌 Variability & Shape
📌 Probability Theory
📌 Hypothesis Testing
Power Bi
📌 Power BI Interface
📌 Data Importing
📌 Data Modeling
📌 Relationships
📌 DAX Basics
📌 Measures & Calculated Columns
📌 Reports
📌 Dashboards
📌 Visual Interactions
📌 Publishing Reports
ETL in Power BI
📌 Data Extraction
📌 Power Query
📌 Data Transformation
📌 Data Cleaning
📌 Data Normalization
📌 Data Loading
📌 Data Refresh
📌 Automation Basics
📌 Data Pipelines Concepts
Data Modeling in Power BI
📌 Data Modeling Concepts
📌 Star Schema
📌 Snowflake Schema
📌 Fact & Dimension Tables
📌 Relationships Management
📌 Cardinality
📌 Cross Filtering
📌 Performance Optimization
📌 Model Validation
Data Analysis and Visualization with Power BI
📌 Visualization Types
📌 Dashboard Design
📌 UX/UI for Dashboards
📌 Interactive Reports
📌 Drill Down & Drill Through
📌 Filters & Slicers
📌 Data Storytelling
📌 KPI Visualization
Tableau for Data Analysis
📌 Tableau Interface
📌 Data Connections
📌 Data Preparation
📌 Worksheets
📌 Dashboards
📌 Story Points
📌 Calculated Fields
📌 Parameters
📌 Filters
📌 Visual Analytics
📌 Tableau Publishing
Who can join
💻 You must own a computer
🎓 No prerequisites required, the diploma takes you from beginner to professional level
🔥 Passion to learn programming and data analysis
Program overview
This comprehensive diploma is designed to equip participants with the skills and tools required to excel in the field of data analysis. The curriculum blends fundamental concepts with hands-on practice using industry-standard tools such as Python, Excel, SQL, Power BI, and Tableau.
Through workshops, assignments, and real projects, you will learn how to clean data, analyze trends, build dashboards, and communicate insights effectively. By the end of the diploma, you will be ready to work confidently as a professional data analyst in real business environments
