Data Analysis using Python (60 Hours)

Objective

Master Python for data cleaning, analysis, and visualization.

Topics Covered

Introduction to Python for Data Analysis

Installing Python, Jupyter Notebook, Anaconda

Python syntax, variables, and data types

Data Structures & Operations

Lists, Tuples, Sets, Dictionaries

Loops, Conditional Statements

NumPy for Numerical Computing

Arrays, Indexing, Slicing, Mathematical Operations

Pandas for Data Analysis

DataFrames, Series, Importing & Exporting Data

Data Cleaning: Handling Missing Values, Duplicates

GroupBy, Merge, Join, Pivot Tables

Data Visualization

Using Matplotlib & Seaborn

Plotting graphs, charts, and trends

Mini Project

Analyze and visualize a real dataset (CSV/Excel)

Data Analysis using SQL (20 Hours)

Objective

Understand relational databases and perform analytical SQL queries.

Topics Covered

Introduction to Databases & DBMS

SQL Basics: SELECT, WHERE, ORDER BY, GROUP BY

Filtering, Sorting, and Joins

Aggregations (SUM, COUNT, AVG, MAX, MIN)

Subqueries and Nested Queries

Creating Views and Reports

Database Functions for Analysis

Integrating SQL with Excel/Python

Hands-On Practice

Write queries for sales, HR, and finance datasets

Build a summary report from multiple tables

Data Analysis using Power BI (35 Hours)

Objective

Visualize and interpret data using Power BI tools.

Topics Covered

Introduction to Power BI Desktop

Importing Data from Excel, SQL, and Web

Data Cleaning & Transformation using Power Query

Creating Relationships & Data Models

Building Dashboards and Reports

Custom Visuals and Filters

DAX (Data Analysis Expressions) Basics

Publishing and Sharing Dashboards

Practical Work

Create an interactive sales dashboard

Visualize data trends with KPIs and slicers

Data Analysis using Power Query (15 Hours)

Objective

Learn data preparation, cleaning, and transformation for business reporting.

Topics Covered

Overview of Power Query Interface

Data Loading from Multiple Sources

Cleaning & Transforming Data (Remove Errors, Merge Columns)

Advanced Query Functions

Combining and Appending Data

Creating Custom Columns

Exporting Transformed Data to Power BI or Excel

Practical Task

Build an automated data-cleaning workflow using Power Query