Data Analytics Course Syllabus in Chennai at Payilagam

Python in Data Analytics Course

Module 1: Python Introduction, Installation

• ➤ Python Introduction
• ➤ Download Python, Installing Python
• ➤ Verify the Installation
• ➤ Install a Text Editor or IDE (Optional)

Module 2: Data Types

• ➤ Numeric Types
• ➤ Text Type
• ➤ Boolean Type
• ➤ None Type

Module 3: Operators

• ➤ Arithmetic Operators
• ➤ Comparison Operators
• ➤ Logical Operators
• ➤ Assignment Operators
• ➤ Membership Operators
• ➤ Identity Operators

Module 4: Functions

• ➤ Function Call
• ➤ Return Statement
• ➤ Types of Parameters – Default Parameters, Variable Length, Arguments
• ➤ Variable-Length Argument Lists, Lambda Functions, Recursion

Module 5: Flow Control Statements

• ➤ Looping Statements: for, while
• ➤ Conditonal Statements: if, elif, else
• ➤ Exception Handling: try, except, finally
• ➤ Pass Statement
• ➤ Project: Calculator Application

Module 6: List

• ➤ Creating A list
• ➤ Accessing Elements
• ➤ Slicing
• ➤ Modifying Elements
• ➤ Adding Elements
• ➤ Removing Elements
• ➤ Sorting: Bubble Sort, Searching: Binary Search
• ➤ Project: Phone Book Application

Module 7: Tuple

• ➤ Creating a Tuple
• ➤ Accessing Elements
• ➤ Slicing
• ➤ Tuple Packing and Unpacking
• ➤ Immutable Nature
• ➤ Project: Inventory Management Application

Module 8: Set

• ➤ Creating a Set
• ➤ Accessing Elements, Adding Elements, Removing Elements
• ➤ Set Operations
• ➤ Other Set Operations
• ➤ Project: Unique words from a book

Module 9: Dictionary

• ➤ Creating a Dictionary, Accessing Values, Modifying Values
• ➤ Adding New Key-Value Pairs, Removing Key-Value Pairs
• ➤ Dictionary Operations, Nested Dictionaries
• ➤ Project: Student management system

Module 10: Package

• ➤ Creating a Package
• ➤ Importing Modules from a Package
• ➤ Importing the Whole Package
• ➤ Subpackages

Module 11: Python OOPs Introduction

• ➤ Class, object
• ➤ Attributes and Methods
• ➤ Encapsulation
• ➤ Inheritance
• ➤ Polymorphism
• ➤ Abstraction
• ➤ Project: Employee Management System

Module 12: Types of Methods

• ➤ Instance Methods
• ➤ Class Methods
• ➤ Static Methods
• ➤ Special Methods (Magic Methods or Dunder Methods)

Module 13: Exception Handling

• ➤ Try-Except Block
• ➤ Handling Specific Exceptions
• ➤ Else and Finally Blocks
• ➤ Raising and Custom Exceptions

Module 14: File Handling

• ➤ Opening, Reading, Writing from a File, Appending to a File
• ➤ Using with Statements, File Modes
• ➤ Exception Handling for File Operations, Working with Paths
• ➤ Project: CSV File parser application

Module 15: Regular Expression

• ➤ Basics of Regular Expressions
• ➤ Using Regular Expressions in Python
• ➤ Projects:
  • ⭐ Email Validator
  • ⭐ Mobile Number Extractor
  • ⭐ Password Validator

Module 16: Multithreading

• ➤ Creating Threads
• ➤ Thread Synchronization
• ➤ Thread Communication
• ➤ Daemon Threads

Module 17: Using SQLite as an Example

• ➤ Install SQLite
• ➤ Import the SQLite Library
• ➤ Connect to a Database
• ➤ Create a Cursor Object
• ➤ Execute SQL Queries
• ➤ Querying Data
• ➤ Closing the Connection

Module 18: Decorator, Generator Functions

• ➤ Generator Functions
• ➤ Decorator Functions

Power BI in Data Analytics Course

Module 1: Introduction

• ➤ What is Power BI?, Interface Overview
• ➤ Data Import: CSV, Excel, SQL import, Power Query (ETL)

Module 2: Data Import

• ➤ CSV, Excel, SQL import
• ➤ Power Query (ETL)

Module 3: DAX (Basic to Intermediate)

• ➤ Calculated Columns
• ➤ Measures
• ➤ SUM, COUNT, CALCULATE, FILTER

Module 4: Visualizations

• ➤ Bar, Line, Pie
• ➤ Maps
• ➤ Slicers
• ➤ Drill-Through
• ➤ Tooltips

Module 5: Dashboards & Publishing

• ➤ Designing Reports
• ➤ Publishing to Power BI Service
• ➤ Sharing Dashboards
• ➤ Projects:
  • ⭐ Sales Dashboard
  • ⭐ Employee Attrition Dashboard
  • ⭐ Student Performance Dashboard

Tableau in Data Analytics Course

Module 1: Introduction

• ➤ Tableau Interface
• ➤ Worksheets, Dashboards, Stories

Module 2: Connecting Data

• ➤ CSV, Excel, SQL
• ➤ Data Cleaning

Module 3: Visual Analytics

• ➤ Bar/Line Charts
• ➤ Scatter Plots
• ➤ Maps

Module 4: Filters & Parameters, Calculations

• ➤ Calculated Fields
• ➤ Table Calculations

Module 5: Dashboards

• ➤ Layouts
• ➤ Actions (Filter, Highlight, URL)
• ➤ Projects:
  • ⭐ Superstore Sales Insights Dashboard
  • ⭐ HR Hiring & Attrition Dashboard
  • ⭐ Revenue Trend Analysis

Final Project: Student Performance Analytics System

• ➤ Using: Python + NumPy + Pandas + SQL + Power BI/Tableau
• ➤ Import student data, Clean and process, Perform analytics, Visualize in Power BI/Tableau, Generate dashboard reports