Data Analysis Professional Diploma
Description
Outline
Curriculum
Materials
Reviews
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
- 5 Sections
- 37 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- 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 Process
- 1.2Introduction to Statistics and its role in Data Analysis
- 1.3Descriptive Statistics: Mean, Median, Mode, Variance, Standard Deviation
- 1.4Data Distribution: Normal distribution, Skewness, Kurtosis
- 1.5Correlation and Covariance
- 1.6Regression Analysis: Simple Linear Regression
- 1.7Hypothesis Testing: t-test, Chi-square test
- 1.8Confidence Intervals and p-values
- 1.9Practical exercises using Excel and Power BI
- 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
- 2.1Power Query: Data import, cleaning, transformation
- 2.2Combining Queries and Parameterization
- 2.3Power Pivot: Data modeling and relationships
- 2.4PivotTables: Grouping, calculated fields, slicers
- 2.5DAX Essentials: Measures, calculated columns
- 2.6Time Intelligence: YTD, QoQ growth, moving averages
- 2.7Scenario Analysis and What-If Analysis
- 2.8Automation with Macros
- 2.9Data Visualization: Pivot Charts and Dashboard Design
- 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
- 3.1Introduction to Power BI and comparison with Excel
- 3.2Data Loading and Transformation using Power Query
- 3.3Data Modeling: Relationships and best practices
- 3.4Basic Visualizations: Bar, Line, Table, Matrix
- 3.5Advanced Visualizations: Drill-through, Heatmaps, Custom visuals
- 3.6Interactivity: Filters, slicers, bookmarks
- 3.7Deployment: Publishing to Power BI Service
- 3.8Security: Row-Level Security (RLS)
- 3.9Collaboration: Sharing via Microsoft Teams
- 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
- Module 5: Capstone ProjectApply all learned skills in a real-world project: prepare data, build models, design dashboards, and deliver a final presentation.4
Features
- Hands‑on labs and real‑world datasets after every module
- Capstone project reviewed with instructor feedback
- Interactive quizzes reinforce key concepts
- Certificate of Completion
Target Audiences
- Data analysts & BI professionals
- Business users moving into data roles
- Working Professionals
- Students & Recent Graduates
- Career Switchers
Requirements
- Basic Excel skills
- Interest in data analytics
- English proficiency is helpful, as the course is likely delivered in English.
Rounds
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