Curriculum
- 44 Sections
- 229 Lessons
- 20 Weeks
Expand all sectionsCollapse all sections
- Module 1: Excel Basics for BeginnersTools Covered: Microsoft Excel (All Versions)8
- 1.1Understanding Excel Interface and RibbonCopyCopy
- 1.2Working with Workbooks, Worksheets, and CellsCopyCopy
- 1.3Entering and Formatting DataCopyCopy
- 1.4Basic Excel Formulas and Functions (SUM, AVERAGE, MIN, MAX)CopyCopy
- 1.5Using AutoFill and Flash FillCopyCopy
- 1.6Basic Formatting (Fonts, Colors, Borders, Cell Styles)CopyCopy
- 1.7Adjusting Rows, Columns, and Cell SizesCopyCopy
- 1.8Basic Excel Shortcuts for EfficiencyCopyCopy
- Module 2: Data Entry, Cleaning, and FormattingTools Covered: Excel Formatting, Data Cleaning Tools6
- 2.1Data Validation (Drop-down Lists, Restrictions)CopyCopy
- 2.2Conditional Formatting for Data HighlightingCopyCopy
- 2.3Text Functions (LEFT, RIGHT, MID, LEN, TRIM, CONCATENATE)CopyCopy
- 2.4Handling Duplicates and Blank CellsCopyCopy
- 2.5Find and Replace, Go To SpecialCopyCopy
- 2.6Sorting and Filtering Data for Better AnalysisCopyCopy
- Module 3: Working with Formulas and FunctionsTools Covered: Excel Formulas, Logical and Lookup Functions5
- 3.1Understanding Relative, Absolute, and Mixed ReferencesCopyCopy
- 3.2Logical Functions (IF, AND, OR, IFERROR, IFS)CopyCopy
- 3.3Lookup and Reference Functions (VLOOKUP, HLOOKUP, XLOOKUP, INDEX-MATCH)CopyCopy
- 3.4Date and Time Functions (TODAY, NOW, DATEDIF, NETWORKDAYS)CopyCopy
- 3.5Text Manipulation with String Functions (TEXT, UPPER, LOWER, PROPER)CopyCopy
- Module 4: Data Visualization with Charts and GraphsTools Covered: Excel Charts and Graphs5
- 4.1Creating and Customizing Charts (Column, Bar, Line, Pie, Area)CopyCopy
- 4.2Advanced Charting (Combo Charts, Waterfall, Funnel, Histogram, Pareto)CopyCopy
- 4.3Data Labels, Titles, and Formatting TechniquesCopyCopy
- 4.4Using Sparklines for Miniature Charts in CellsCopyCopy
- 4.5Dynamic Charts using Named RangesCopyCopy
- Module 5: Data Analysis with Pivot Tables and Pivot ChartsTools Covered: Excel Pivot Tables and Pivot Charts6
- 5.1Introduction to Pivot Tables and Pivot ChartsCopyCopy
- 5.2Creating Pivot Tables for Data AnalysisCopyCopy
- 5.3Using Slicers and Filters in Pivot TablesCopyCopy
- 5.4Summarizing Data with Pivot TablesCopyCopy
- 5.5Creating Pivot Charts for Better InsightsCopyCopy
- 5.6Grouping and Custom Calculations in Pivot TablesCopyCopy
- Module 6: Advanced Excel Functions for Data AnalysisTools Covered: Excel Advanced Formulas and Functions5
- 6.1Advanced Lookup Functions (XLOOKUP, OFFSET, INDIRECT)CopyCopy
- 6.2Array Formulas and Dynamic Arrays (SORT, FILTER, UNIQUE)CopyCopy
- 6.3Advanced Conditional Formatting for Dynamic Data HighlightingCopyCopy
- 6.4Statistical Functions (COUNTIF, AVERAGEIF, SUMIF, RANK, PERCENTILE, QUARTILE)CopyCopy
- 6.5Data Forecasting and Trend AnalysisCopyCopy
- Module 7: Power Query and Power Pivot for Data ModelingTools Covered: Power Query, Power Pivot5
- 7.1Introduction to Power Query for Data Cleaning and TransformationCopyCopy
- 7.2Importing and Transforming Data using Power QueryCopyCopy
- 7.3Introduction to Power Pivot for Data ModelingCopyCopy
- 7.4Creating Relationships and Measures in Power PivotCopyCopy
- 7.5Using DAX Functions for Data Analysis in Power PivotCopyCopy
- Module 8: Working with Large Datasets and Advanced Excel ToolsTools Covered: Excel Data Management5
- Module 9: Excel for Business Intelligence and ReportingTools Covered: Power BI, Excel Dashboards4
- Module 10: Projects and Interview PreparationTools Covered: Excel, Power Query, Power Pivot4
- SQL Course Curriculum – SQL (Basic to Advanced)A structured learning path for mastering SQL for data analysis, from fundamentals to advanced database querying.0
- Module 11: Introduction to Databases and SQLTools Covered: MySQL, Microsoft SQL Server, PostgreSQL5
- 12.1Understanding Databases and Relational Database Management Systems (RDBMS)CopyCopy
- 12.2Difference Between SQL and NoSQL DatabasesCopyCopy
- 12.3Database Architecture and ACID PropertiesCopyCopy
- 12.4Setting Up MySQL / SQL Server / PostgreSQL EnvironmentCopyCopy
- 12.5Introduction to SQL and Its Role in Data AnalysisCopyCopy
- Module 12: SQL Basics – Writing QueriesTools Covered: SQL Query Editor, MySQL Workbench, SSMS6
- 13.1Introduction to SQL Syntax and Data TypesCopyCopy
- 13.2Creating and Managing DatabasesCopyCopy
- 13.3Creating, Modifying, and Deleting TablesCopyCopy
- 13.4Understanding Primary Keys, Foreign Keys, and ConstraintsCopyCopy
- 13.5Inserting, Updating, and Deleting Records (CRUD Operations)CopyCopy
- 13.6Querying Data using SELECT StatementsCopyCopy
- Module 13: Advanced Data Retrieval and FilteringTools Covered: SQL Querying Tools5
- Module 14: Aggregations and Grouping DataTools Covered: SQL Functions and Queries4
- Module 15: Working with Joins and RelationshipsTools Covered: SQL Joins and Relationships5
- Module 16: Advanced SQL for Data AnalysisTools Covered: SQL Advanced Queries5
- 17.1Using String Functions (CONCAT, SUBSTRING, REPLACE, CHARINDEX)CopyCopy
- 17.2Date and Time Functions (NOW, DATEADD, DATEDIFF)CopyCopy
- 17.3Handling Complex Queries using CTEs and Recursive QueriesCopyCopy
- 17.4Pivoting Data for Business Intelligence ReportsCopyCopy
- 17.5Ranking and Analytical FunctionsCopyCopy
- Module 17: SQL Performance Optimization and IndexingTools Covered: SQL Server / MySQL Performance Tools5
- Module 18: SQL for Data Analysis and ReportingTools Covered: SQL Reporting and Visualization4
- Module 19: Real-World Projects and Interview PreparationTools Covered: SQL, Power BI, Excel4
- Power BI Course Curriculum (Beginner to Advanced)A structured approach for mastering Power BI with real-world projects and interview preparation.0
- Module 20: Quick Start with Power BI ServiceTools Covered: Power BI Service, Power BI Desktop6
- 22.1Getting Power BI Tools: Installing and Setting UpCopyCopy
- 22.2Introduction to Power BI Components and TerminologyCopyCopy
- 22.3Creating a Dashboard in Minutes (Hands-on Exercise)CopyCopy
- 22.4Refreshing Data in Power BI ServiceCopyCopy
- 22.5Interacting with Dashboards and ReportsCopyCopy
- 22.6Sharing Dashboards and ReportsCopyCopy
- Module 21: Getting and Transforming Data with Power BI DesktopTools Covered: Power BI Desktop, Power Query Editor6
- 23.1Introduction to Power BI DesktopCopyCopy
- 23.2Getting Data: Excel vs Power BI Desktop and ServiceCopyCopy
- 23.3Understanding Data Structure for Q&ACopyCopy
- 23.4Direct Query vs Import DataCopyCopy
- 23.5Connecting to Multiple Data SourcesCopyCopy
- 23.6Data Cleaning and Transformation using Power QueryCopyCopy
- Module 22: Data Modeling in Power BITools Covered: Power BI Desktop7
- 24.1Introduction to Data ModelingCopyCopy
- 24.2Setting Up and Managing RelationshipsCopyCopy
- 24.3Understanding Cardinality and Cross-FilteringCopyCopy
- 24.4Default Summarization and Sorting OptionsCopyCopy
- 24.5Creating Calculated ColumnsCopyCopy
- 24.6Creating Measures and Quick MeasuresCopyCopy
- 24.7Optimizing Data Models for PerformanceCopyCopy
- Module 23: Data Visualization in Power BITools Covered: Power BI Desktop20
- 25.1Creating Different Types of VisualizationsCopyCopy
- 25.2Formatting and Customizing VisualizationsCopyCopy
- 25.3Setting Sort Order for VisualsCopyCopy
- 25.4Using Scatter and Bubble Charts with Play AxisCopyCopy
- 25.5Tooltips and Interactive ReportsCopyCopy
- 25.6Slicers, Timeline Slicers, and Sync SlicersCopyCopy
- 25.7Cross Filtering and HighlightingCopyCopy
- 25.8Applying Visual, Page, and Report Level FiltersCopyCopy
- 25.9Drill Down and Drill Up FunctionalityCopyCopy
- 25.10Working with HierarchiesCopyCopy
- 25.11Adding Reference and Constant LinesCopyCopy
- 25.12Creating Tables and Matrices with Conditional FormattingCopyCopy
- 25.13Using KPI Indicators, Cards, and GaugesCopyCopy
- 25.14Map VisualizationsCopyCopy
- 25.15Importing and Using Custom VisualsCopyCopy
- 25.16Managing and Arranging Visuals in ReportsCopyCopy
- 25.17Implementing Drill-through for In-depth AnalysisCopyCopy
- 25.18Using Custom Report ThemesCopyCopy
- 25.19Grouping and Binning DataCopyCopy
- 25.20Working with Selection Pane, Bookmarks, and ButtonsCopyCopy
- Module 24: Power BI Service Visualization ToolsTools Covered: Power BI Service5
- Module 25: Publishing and Sharing ReportsTools Covered: Power BI Service, Power BI Desktop13
- 27.1Introduction to Power BI Publishing and Sharing OptionsCopyCopy
- 27.2Overview of Different Sharing MethodsCopyCopy
- 27.3Publishing Reports from Power BI DesktopCopyCopy
- 27.4Publishing Reports to the WebCopyCopy
- 27.5Sharing Dashboards with Power BI ServiceCopyCopy
- 27.6Creating and Managing Workspaces and Apps (Power BI Pro)CopyCopy
- 27.7Using Content Packs (Power BI Pro)CopyCopy
- 27.8Printing or Saving Reports as PDFsCopyCopy
- 27.9Implementing Row-Level Security (Power BI Pro)CopyCopy
- 27.10Exporting Data from VisualizationsCopyCopy
- 27.11Publishing Reports for Mobile ApplicationsCopyCopy
- 27.12Exporting Reports to PowerPointCopyCopy
- 27.13Summary of Sharing OptionsCopyCopy
- Module 26: Data Refresh and Gateway SetupTools Covered: Power BI Service, On-Premises Gateway5
- Module 27: Power BI and Excel IntegrationTools Covered: Power BI Desktop, Power BI Service, Excel5
- 29.1Different Options for Publishing Data from Excel to Power BICopyCopy
- 29.2Pinning Excel Elements to Power BI DashboardsCopyCopy
- 29.3Connecting Excel Data using Power BI Publisher and Analyze in ExcelCopyCopy
- 29.4Publishing Excel Dashboards to Power BICopyCopy
- 29.5Uploading and Exporting Excel Data to Power BICopyCopy
- Module 28: Power BI Projects and Interview PreparationTools Covered: Power BI Desktop, Power BI Service4
- Tableau Mastery (Optional**): Data Visualization and Business Intelligence0
- Module 29: Introduction to Tableau and BI Concepts6
- 32.1Overview of Data Warehousing and Business IntelligenceCopyCopy
- 32.2Fundamentals of Data Analysis and VisualizationCopyCopy
- 32.3Business Reporting and Dashboard EssentialsCopyCopy
- 32.4Introduction to Tableau and Its ArchitectureCopyCopy
- 32.5Understanding Measures vs. DimensionsCopyCopy
- 32.6Continuous vs. Discrete Data, Value & Category AxesCopyCopy
- Module 30: Connecting and Managing Data Sources4
- Module 31: Saving and Publishing Workbooks3
- Module 32: Core Data Visualization Techniques5
- Module 33: Creating Effective VisualizationsBuilding Various Chart Types:6
- 36.1Line, Bar, Stacked, and Dual-Axis ChartsCopyCopy
- 36.2Heat Maps, Text Tables, and Highlight TablesCopyCopy
- 36.3Symbol and Filled Maps, Pie Charts, and TreemapsCopyCopy
- 36.4Symbol and Filled Maps, Pie Charts, and TreemapsCopyCopy
- 36.5Symbol and Filled Maps, Pie Charts, and TreemapsCopyCopy
- 36.6Gantt, Bullet, and Packed Bubble ChartsCopyCopy
- Module 34: Advanced Features and Analytics7
- 37.1Designing Interactive DashboardsCopyCopy
- 37.2Forecasting and Trend AnalysisCopyCopy
- 37.3Adding Reference Lines, Bands, and Visual HighlightsCopyCopy
- 37.4Handling Missing Values and Null DataCopyCopy
- 37.5Implementing Table Calculations and TotalsCopyCopy
- 37.6Custom Formatting, Annotations, and Layout AdjustmentsCopyCopy
- 37.7Using Dashboard Actions: Filters and HighlightsCopyCopy
- Module 35: Tableau Server and Collaboration4
- Module 36: Project Work and Interview Preparation3
- Module 37: Requirement Gathering and Process DocumentationTopics Covered:6
- 40.1BRD: Define scope, objectives, stakeholders; write clear needs.CopyCopy
- 40.2FRD: Specify features, workflows; link to BRD.CopyCopy
- 40.3Process Modeling: Use BPMN (tasks, events); create flowcharts.CopyCopy
- 40.4Elicitation: Conduct interviews, prioritize with MoSCoW.CopyCopy
- 40.5Practical Application:CopyCopy
- 40.6Draft BRD/FRD for an order system; model its process with a flowchart.CopyCopy
- Module 38: Agile and Collaboration ToolsTopics Covered:3
- Module 39: Design, Presentation, and AI IntegrationTopics Covered:5
- 42.1Wireframes (Figma): Create basic layouts for business solutions.CopyCopy
- 42.2Presentation (Canva): Design slides to communicate insights.CopyCopy
- 42.3AI Insights/Automation: Use AI tools (e.g., ChatGPT) for drafting or insights.CopyCopy
- 42.4Practical Application:CopyCopy
- 42.5Design a wireframe (Figma) and presentation (Canva) for a BA deliverable; enhance with AI-generated insights.CopyCopy
- Capstone Project5
- Perks & Benefits5
Working with Workbooks, Worksheets, and CellsCopyCopy
Next
