Excel Fundamentals

• Excel Interface Overview
• Workbook & Worksheet Structure
• Basic Formatting
• Basic Formulas: SUM, AVERAGE, MIN, MAX, COUNT, COUNTA
• Conditional Functions: IF, AND, OR, Nested IF
• Text Functions:LEFT, RIGHT, MID, LEN, CONCAT, UPPER, LOWER, PROPER, TRIM

Excel Advanced

• Lookup Functions: VLOOKUP, HLOOKUP
• XLOOKUP, INDEX + MATCH Data Cleaning
• Techniques: Remove Duplicates, Find & Replace
• Flash Fill, Text to Columns Sorting
• Filtering & Advanced Filters Conditional
• Formatting Pivot Tables – Grouping
• Summaries, Calculated Fields Charts
• Visualization: Line, Bar, Pie, Combo Charts

Introduction

• What is Machine Learning?
• Types of Machine Learning:
• Supervised, Unsupervised, Reinforcement Learning
• Applications of ML in Real World
• Overview of ML Workflow (Data → Model → Evaluation → Deployment)

Data Preprocessing & Feature Engineering

• Importing and Exploring Datasets
• Handling Missing Values, Outliers, and Duplicates
• Encoding Categorical Data (One-Hot, Label Encoding)
• Feature Scaling: Normalization & Standardization
• Train-Test Split & Cross-Validation
• Feature Selection Techniques

Supervised Learning – Regression

• Simple & Multiple Linear Regression
• Polynomial Regression
• Evaluation Metrics: MAE, MSE, RMSE, R² Score
• Regularization: Lasso, Ridge, ElasticNet

Supervised Learning – Classification

• Logistic Regression
• k-Nearest Neighbors (kNN) Decision Trees &
• Random Forests Support Vector Machines (SVM)
• Evaluation Metrics: Confusion Matrix,
• Accuracy, Precision, Recall, F1-Score ROC
• Curve & AUC

Unsupervised Learning

• Clustering Techniques:
• K-Means, Hierarchical Clustering
• Dimensionality Reduction: PCA, t-SNE
• Anomaly Detection & Association Rules
• Use Cases & Hands-on Implementation

Introduction & Setup

• Introduction to Power BI & Its
• Components Power Query, Data Model,
• DAX, Reports Installing Power BI
• Desktop Getting Familiar with the Interface
• Importing Data from Excel / CSV / SQL

Data Cleaning & Transformation (Power Query)

• Power Query – Data Cleaning Remove
• Rows, Fill, Replace, Split Columns
• Column Transformations Merge
• Append, Unpivot Basic Data Profiling (Errors & Nulls Handling)

Functions

• Function declaration & expression
• Parameters & return values
• Arrow functions

Data Modeling & Relationships

• Understanding Relationships
• One-to-Many, Many-to-Many
• Star Schema vs Snowflake Schema
• Creating Optimized Data Models

DAX Calculations & Logic

• DAX Basics – Calculated Columns vs Measures
• Aggregation Functions – SUM, COUNT, AVERAGE, DISTINCTCOUNT
• Conditional Logic – IF, SWITCH, CALCULATE, FILTER
• Advanced DAX Functions (Time Intelligence, Ranking, Cumulative Analysis)

Data Visualization & Reporting

• Power BI Visualization Basics
• Bar, Column, Line Charts
• Pie, Donut, Waterfall, KPI Cards
• Maps, Matrix, Slicers, Drill-Down Reports
• Designing Interactive Dashboards
• Layout, Theme, Bookmarks

Advanced Concepts

• How to Build & Publish Dashboards
• Power BI Service (My Workspace)
• Subscriptions & Data Refresh
• Alerts, Gateway Setup

SQL Basics & Data Retrieval

• Introduction to Databases & SQL
• RDBMS Concepts, Tables, Primary & Foreign Keys
• Basic Queries: SELECT, FROM, WHERE – Filtering Records
• Sorting & Limiting Data: ORDER BY, LIMIT
• Removing Duplicates: DISTINCT
• Practice Queries / Assignments

Operators & Conditional Filtering

• Basic Operators: BETWEEN, IN, LIKE, IS NULL
• Combining Conditions: AND, OR, NOT
• Practice Queries / Mini Assignments

Aggregation & Grouping

• Aggregate Functions: SUM, COUNT, AVG, MIN, MAX
• Grouping Data: GROUP BY, HAVING (Advanced Filtering)
• Practice Queries / Case Study

Joins & Relationships

• Understanding Joins: INNER JOIN
• LEFT JOIN, RIGHT JOIN
• FULL OUTER JOIN
• Practice Queries / Multiple Table Scenarios

Advanced SQL Queries

• Set Operations: UNION vs UNION ALL
• Conditional Logic with CASE WHEN
• Subqueries: IN, EXISTS, SELECT within SELECT
• Window Functions: ROW_NUMBER, RANK, DENSE_RANK
• Practice Queries / Problem Solving

Optimization & Views

• Creating and Using Views
• Indexing Basics for Performance
• Best Practices for Query Optimization
• Final Practice Queries / Mini Project

Python Fundamentals

• Data Types – Numbers, Strings, Lists
• Tuples, Dictionaries, Sets
• Conditional Statements (if-else) & Loops (for, while)
• Functions, Lambda Functions, Modules

Numpy

NumPy – Numerical Computing

• Introduction to NumPy Arrays, Array Creation
• Array Indexing & Slicing
• Array Operations: Math, Aggregations, Broadcasting
• Reshaping, Stacking, Splitting Arrays

Pandas

Pandas – Data Manipulation (Basics)

• Series & DataFrame Basics
• Importing Data (CSV, Excel), Viewing & Describing Data
• Filtering, Sorting, Conditional Selection

Pandas – Data Manipulation (Advanced)

• GroupBy, Aggregations
• Merge & Join DataFrames
• Handling Missing Values & Data Cleaning

Data Visualization

• Introduction to Matplotlib: Line, Bar, Scatter
• Histogram, Pie, Subplots
• Seaborn Basics: Heatmap, Boxplot