Data Analysis Professional Diploma
Course Overview
Turn data into insight using Excel, Power BI, and Microsoft Fabric. Prepare, model, visualize, and analyze data with hands-on labs and a capstone project.
This course is designed for those who perform data analysis tasks and want to enhance their skills using Power BI.
Course Objectives
By the end of this course, you will be able to:
1.Prepare & transform data from diverse sources.
2.Model data with star‑schema design and robust DAX.
3.Build and share interactive dashboards, reports.
4.Apply advanced analytics (AI visuals, clustering, insights).
5.Manage, secure & automate content in the Power BIService.
6.Leverage Copilot & Microsoft Fabric for end‑to‑endanalytics.
Capstone Project
Participants will work in groups to create and present a full digital marketing campaign tailored to product or service. Projects will include strategy, platform selection, content samples, KPIs, and media budgeting.
Module 1: Statistics for Data Analysis – 9 hours
- Data Analysis Fundamentals and Process
- Introduction to Statistics and its role in Data Analysis
- Descriptive Statistics: Mean, Median, Mode, Variance, Standard Deviation
- Data Distribution: Normal distribution, Skewness, Kurtosis
- Correlation and Covariance
- Regression Analysis: Simple Linear Regression
- Hypothesis Testing: t-test, Chi-square test
- Confidence Intervals and p-values
- Practical exercises using Excel and Power BI
Module 2: Data Analysis in Excel – 21 hours
- Power Query: Data import, cleaning, transformation
- Combining Queries and Parameterization
- Power Pivot: Data modeling and relationships
- PivotTables: Grouping, calculated fields, slicers
- DAX Essentials: Measures, calculated columns
- Time Intelligence: YTD, QoQ growth, moving averages
- Scenario Analysis and What-If Analysis
- Automation with Macros
- Data Visualization: Pivot Charts and Dashboard Design
Module 3: Power BI Analytics – 18 hours
- Introduction to Power BI and comparison with Excel
- Data Loading and Transformation using Power Query
- Data Modeling: Relationships and best practices
- Basic Visualizations: Bar, Line, Table, Matrix
- Advanced Visualizations: Drill-through, Heatmaps, Custom visuals
- Interactivity: Filters, slicers, bookmarks
- Deployment: Publishing to Power BI Service
- Security: Row-Level Security (RLS)
- Collaboration: Sharing via Microsoft Teams
Module 4: Advanced Power BI & AI – 6 hours
- Advanced DAX Patterns and Performance Optimization
- Composite Models and Aggregations
- AI Visuals: Key Influencers, Decomposition Tree
- Predictive Analytics with Power BI
- Integration with Microsoft Fabric
- Automation and Governance in Power BI Service
Module 5: Capstone Project – 6 hours
- Data Preparation
- Model Development
- Final Presentation
Curriculum
- 11 Sections
- 41 Lessons
- 10 Weeks
- Module 1: Statistics for Data AnalysisLearn core statistical concepts for data analysis, including descriptive statistics, data distribution, correlation, regression, and hypothesis testing. Apply techniques through practical exercises in Excel and Power BI.9
- 1.1Data Analysis Fundamentals and ProcessCopy
- 1.2Introduction to Statistics and its role in Data AnalysisCopy
- 1.3Descriptive Statistics: Mean, Median, Mode, Variance, Standard DeviationCopy
- 1.4Data Distribution: Normal distribution, Skewness, KurtosisCopy
- 1.5Correlation and CovarianceCopy
- 1.6Regression Analysis: Simple Linear RegressionCopy
- 1.7Hypothesis Testing: t-test, Chi-square testCopy
- 1.8Confidence Intervals and p-valuesCopy
- 1.9Practical exercises using Excel and Power BICopy
- Quiz – Statistics for Data AnalysisA short quiz designed to assess your understanding of key statistical concepts used in data analysis.1
- Module 2: Data Analysis in ExcelMaster advanced Excel tools for data analysis: Power Query, Power Pivot, PivotTables, DAX basics, time intelligence, scenario analysis, automation with macros, and dashboard design.9
- 3.1Power Query: Data import, cleaning, transformationCopy
- 3.2Combining Queries and ParameterizationCopy
- 3.3Power Pivot: Data modeling and relationshipsCopy
- 3.4PivotTables: Grouping, calculated fields, slicersCopy
- 3.5DAX Essentials: Measures, calculated columnsCopy
- 3.6Time Intelligence: YTD, QoQ growth, moving averagesCopy
- 3.7Scenario Analysis and What-If AnalysisCopy
- 3.8Automation with MacrosCopy
- 3.9Data Visualization: Pivot Charts and Dashboard DesignCopy
- Quiz – Excel for Data AnalysisA hands‑on practice to ensures learners develop the foundational Excel competency needed for more advanced analytical tools1
- Module 3: Power BI AnalyticsExplore Power BI for data visualization and reporting. Learn data loading, modeling, interactive dashboards, advanced visuals, publishing to Power BI Service, and collaboration features.9
- 5.1Introduction to Power BI and comparison with ExcelCopy
- 5.2Data Loading and Transformation using Power QueryCopy
- 5.3Data Modeling: Relationships and best practicesCopy
- 5.4Basic Visualizations: Bar, Line, Table, MatrixCopy
- 5.5Advanced Visualizations: Drill-through, Heatmaps, Custom visualsCopy
- 5.6Interactivity: Filters, slicers, bookmarksCopy
- 5.7Deployment: Publishing to Power BI ServiceCopy
- 5.8Security: Row-Level Security (RLS)Copy
- 5.9Collaboration: Sharing via Microsoft TeamsCopy
- Module 4: Advanced Power BI & AIEnhance Power BI skills with advanced DAX, composite models, AI visuals, predictive analytics, integration with Microsoft Fabric, and governance best practices.6
- Quiz – Power BI AnalyticsA practical training session covering Power Query fundamentals to ensure a solid understanding of essential data modeling concepts.1
- Module 5: Capstone ProjectApply all learned skills in a real-world project: prepare data, build models, design dashboards, and deliver a final presentation.4
- Official Microsoft Learning Material aligned with PL‑300 ExamAligned learning content covers the PL‑300 exam objectives. Learners will follow to ensure accurate, up‑to‑date, and exam‑relevant preparation.0
- Practice Assessment for PL‑300 Power BI Certified AnalystsA focused practice assessment that simulates PL‑300 exam-style questions across Power BI data preparation, modeling, visualization, and deployment—helping learners gauge readiness and identify areas for improvement.1
- Recorded Sessions4
Mohamed Yahia
Professional Summary
Mohamed Yahia is a Certified Management Accountant (CMA) and Microsoft/IBM-certified Data Analyst with 15+ years of corporate expertise in financial analysis, budgeting, and data-driven decision-making. As a Budget & Financial Analysis Manager at Telecom Egypt, he oversees multi-million-dollar budgets, designs executive dashboards, and transforms raw data into strategic insights using Power BI, Excel, and SQL.
A dedicated educator, Mohamed has 5+ years of training experience, teaching professionals to master financial modeling, Power BI visualization, and advanced Excel techniques. His unique blend of CMA expertise (Master’s in Accounting) and cutting-edge data certifications (Nanodegree, IBM, Microsoft) bridges the gap between finance and analytics.
Key Qualifications
• Power BI & Excel: 15+ years building dynamic reports, KPIs, and forecasting models.
• Certifications: Microsoft Certified: Power BI Data Analyst Associate | IBM Data Analyst Professional Certificate | Udacity Nanodegree.
• Taught 100+ professionals to pass CMA exams and deploy Power BI/Excel solutions.
• Winner of Telecom Egypt’s Leadership Award for data-driven presentations.
Education & Certifications
• Certified Management Accountant (CMA)
• Master’s in Accounting (Damanhour University)
• Microsoft Certified: Power BI Data Analyst Associate
• IBM Data Analyst Professional Certificate | Udacity Data Analyst Nanodegree
• IBM Data Analyst Professional Certificate
• Data Analyst Nano Degree.
- Hands‑on labs and real‑world datasets after every module
- Capstone project reviewed with instructor feedback
- Interactive quizzes reinforce key concepts
- Certificate of Completion
- Data analysts & BI professionals
- Business users moving into data roles
- Working Professionals
- Students & Recent Graduates
- Career Switchers
- Basic Excel skills
- Interest in data analytics
- English proficiency is helpful, as the course is likely delivered in English.
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