1. Introduction to Excel

// Excel Interface (Ribbon, Toolbar, Sheets, Cells)

// Creating, Opening, and Saving Workbooks

// Understanding Rows, Columns, and Cells

// Basic Formulas & Functions

// Arithmetic Operations (+, -, *, /)

// Common Functions Aggregate functions

// Working with Multiple Sheets

// Adding, Renaming, Deleting Sheets

// Linking Data Between Sheets (Sheet1!A1)

// Freezing Panes & Splitting Windows

2.Basic Data Analysis Tools

// PivotTables (Summarizing Data)

// Basic PivotChart Creation

// Introduction to Flash Fill & Quick Analysis

// VLOOKUP (Finding values in a table)

// HLOOKUP (Horizontal Lookup)

// XLOOKUP (Advanced Lookup – newer versions)

// INDEX & MATCH (Flexible lookup alternative)

3.Basic Keyboard Shortcuts

4.External Data Connections

5.Power Queries

6.Power Pivot

Introduction to SQL & Databases

• What is SQL?

• Relational Database Concepts (Tables, Rows, Columns, Keys)

• SQL Server Overview (SSMS, Azure SQL)

Data Retrieval – SELECT Statement

• Basic SELECT queries

• Filtering data using WHERE

• Sorting data with ORDER BY

• Using DISTINCT to remove duplicates

Working with SQL Functions

• Aggregate Functions (SUM, AVG, COUNT, MIN, MAX)

• String Functions (LEN, UPPER, LOWER, SUBSTRING)

• Date Functions (GETDATE, DATEADD, DATEDIFF)

Filtering & Conditional Logic

• Using WHERE, AND, OR, BETWEEN, IN, LIKE

• Using CASE for conditional output

Joins & Relationships

• Inner Join (INNER JOIN)

• Outer Joins (LEFT JOIN, RIGHT JOIN, FULL JOIN)

• Cross Join & Self Join

Grouping & Aggregation

• GROUP BY and HAVING clauses

• Using ROLLUP and CUBE for multi-level aggregations

Modifying Data

• INSERT INTO (Adding Data)

• UPDATE (Modifying Data)

• DELETE (Removing Data)

• Using TRUNCATE vs DELETE

Views & Indexing

• Creating and Managing VIEWS

• Understanding Indexes (CLUSTERED, NONCLUSTERED)

Stored Procedures & Functions (Basic Level)

• Creating & Executing Stored Procedures

• User-Defined Functions (Scalar, Table-Valued)

Transactions & Error Handling

• Understanding COMMIT and ROLLBACK

• Using TRY...CATCH for error handling

Introduction

• Understanding Power BI Desktop vs. Power BI Service vs. Power BI Mobile

• Installation and setup

• Power BI user interface overview

Data Connections

• Connecting to various data sources

-Excel, SQL Server, Sharepoint, Folders, Web, etc

• Import vs. Direct Query mode

Data Transformation and Cleaning - Power Query

• Merge Queries

• Append Queries

• Invoke Custom Functions

• Pivot, Unpivoting, Transpose

• Text Functions, Formatting

• Calculations

• Power Query Advance editor

Data Modelling

• Optimizing data by hiding unnecessary fields

• Defining relationships between tables

• Cross Filters

• Creating calculated columns and measures,

• What is Star Schema

• What is Snowflake Schema

DAX (Data Analysis Expressions)

• Calculated columns

• Time intelligence functions

• Mathematical and trigonometric functions

• Table functions

• Calculated Measures

• Lookupvalue

• Filters

• Declaring Variables

• Usage of UNICHAR

• Formatting through DAX

Creating Visualizations

• Types of visualizations (bar charts, line charts, maps, pie charts , matrix etc.)

• Customizing visuals (colors, labels, themes)

• Using slicers, filters, buttons and drill-throughs

• Interactive features (cross-filtering, sync slicers, tooltips, bookmarks)

• Report layout and design best practices

• Incorporating text boxes, images, and shapes

• Using Power BI templates

• Importing and using custom visuals from AppSource

Row-Level Security (RLS) & Page Level Securities (PLS)

• Setting up RLS/PLS in Power BI

• Creating roles and assigning users

• Testing and validating RLS

Dashboards and Power BI Service

• Difference between reports and dashboards

• Pinning visuals to dashboards

• Real-time dashboards and live data

• Sharing and collaborating on dashboards

Performance Optimization

• Use the Performance Analyzer

• Optimize queries

• Optimize data models

Advanced Analytics with Power BI

• Integrating Python scripts

Power BI Governance and Administration

• Key aspects of Power BI Governance and Administration

• How to implement Power BI Governance

• Benefits of good Power BI Governance

1. Introduction:

• Variables and Data Types (int, float, string, list, tuple, dict, set)

• Conditional Statements (if-else)

• Loops (for, while)

• Functions and Lambda Functions

• List Comprehensions

2. Working with Libraries

• NumPy: Arrays, mathematical operations, indexing, reshaping

• Pandas: DataFrames, Series, reading/writing CSV & Excel, filtering, grouping

• Matplotlib & Seaborn: Data visualization, plots, charts

3. Data Manipulation & Cleaning

• Handling missing data

• Data transformation (scaling, normalization)

• Merging, joining, and pivoting tables

• Handling categorical and datetime data

4. Exploratory Data Analysis (EDA)

• Summary statistics

• Correlations and distributions

• Detecting outliers

5. Data Visualization

• Line plots, bar charts, histograms

• Heatmaps, scatter plots, box plots

• Customizing plots with Seaborn & Matplotlib

6. Statistical Concepts

• Mean, Median, Mode

• Variance & Standard Deviation

• Probability distributions

• Hypothesis Testing

7. Machine Learning Basics (Optional Beginner Topics)

• Linear & Logistic Regression

• Decision Trees

• Clustering (K-Means)

• Train-test split and model evaluation