🔹 Data Analyst Course Content

1. Fundamentals of Data Analyst

• What is Data Science?
• Need for Data Scientists
• Foundation, Business Intelligence, Analytics
• Data Analysis & Mining, Machine Learning
• Types of Analytics, Analytics Project Lifecycle
• Data Types, Categorization, Collection

2. Excel

• Intro to Excel, Rows & Columns
• Ranges, Basic & Advanced Formulas
• Data Analysis, Pivot Tables, Power Pivot
• Spreadsheet Tools, Cleaning, Validation
• Excel Visualization

3. Database / SQL

• Intro to RDBMS & SQL
• DDL, DML, DQL, TCL, DCL commands
• Datatypes, Create/Alter/Drop
• SELECT queries, WHERE, Operators
• Union, Join, GroupBy, Set Operators

4. Statistical Analysis

• Descriptive & Inferential Statistics
• Probability, Distributions, Sampling, ANOVA
• Hypothesis Testing, Linear Regression
• Prediction Analytics, Model Building

5. R Programming & Visualization

• R Basics: Vectors, Matrices, Data Frames
• Control Structures, Functions
• Subsetting, Vectorized Operations
• Import/Export Data, DPLYR & Data Cleaning
• Data Visualization, Plots, Customization

6. Python

• Python Overview, Variables, Functions
• Strings, Loops, Sequences, File IO
• Data Structures, Comprehensions, Generators

7. Machine Learning Overview

• Supervised & Unsupervised Learning
• Regression, Classification, Clustering
• K-Means, Decision Trees, Random Forests
• Text Mining, Sentiment Analysis

8. Power BI / Tableau

• Power BI Desktop & Service
• Query, Data Transformation, DAX
• Data Modeling, Visualizations, Reports

9. Projects (Elective)

• Facial Recognition, Social Media Analytics
• Object Detection, Sales Prediction
• Stock Market, Data Security, Handwriting Recognition