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Data Science
Curriculum
5 Sections
5 Lessons
30 Hours
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Module 1 – Data Management in Excel – 4 hours
1
1.1
Data Cleaning and Preparation, Working with Large Datasets, Advanced Filtering and Sorting Techniques, Using Excel Tables for Data Management, Data Consolidation and AnalysisCopyCopyCopyCopyCopyCopy
Module 2 – Data Analysis and Visualization – 6 hours
1
2.1
PivotTables and Pivot Charts, Slicers and Timelines, Data Analysis Tools: Using Goal Seek, Solver, and Data Tables for scenario analysis. Conditional Formatting: Advanced techniques for highlighting data patterns and trends. Advanced Charting: Creating and customizing advanced chart types (e.g., Waterfall, Funnel, Combo Charts).CopyCopyCopyCopyCopyCopy
Module 3 – Excel formulas and data analysis – 10 hours
1
3.1
Logical formulas on excel, Math formulas in excel, Lookup and Reference formulas in excel, Stats formulas in excel, Text formulas in excel, Date and Time formulas in excel, Formulas mix and match (10 examples), Named ranges in excel, Data validation in excel, What-If Analysis: Using Data Tables, Scenario Manager, and Goal Seek for advanced what-if analysis, Data Consolidation, Dashboard Creation.CopyCopyCopyCopyCopyCopy
Module 4 – Introduction to Power BI – 5 hours
1
4.1
Getting Started with Power BI Desktop, Importing and Transforming Data, Data Modeling in Power BI, Creating Basic Visualizations, Publishing Reports to Power BI ServiceCopyCopyCopyCopyCopyCopy
Module 5 – Advanced Power BI Techniques – 5 hours
1
5.1
Advanced Data Modeling (DAX, Calculated Columns, Measures), Advanced Visualization Techniques, Using Power Query for Data Transformation, Custom Visuals in Power BI, Power BI Integration with Excel, Using Excel as a Data Source for Power BI, Case Studies and Project Work.CopyCopyCopyCopyCopyCopy
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