1: DATA ANALYTICS

 A: INTRODUCTION TO DATA ANALYTICS

•       What is Data Analytics?

•       Why Data Analytics?

•       Difference between Data Analytics and Data Science

•       Applications of Data Analytics

•       Scope of Data Analytics

•       What is Data Collection?

•       What is Data Cleaning?

•       What is Data Analysis?

•       Tools required for Data Analytics

 B: DATA ANALYTICS USING SQL

•       Understanding SQL, Databases and Tables

•       Understanding MySQL

•       Downloading and Installing MySQL

•       Types of SQL Commands: DDL, DML and DQL Commands

•       DDL Commands: create database query, create table query, drop database query, drop table query, alter table query

•       DML Commands: insert query, update query, delete query

•       DQL Commands: select query, select distinct queries, select where, order by, group by, having queries, select limit, operators in select query

•       SQL Constraints: not null, unique, check, primary key

•       SQL Keys: Unique, Primary, Foreign, Composite and Candidate

•       SQL Functions: count(), sum(), avg(), min() and max()

•       Data and Time Functions in SQL

•       Writing Conditional Queries

•       Writing Subqueries in SQL

•       SQL Joins: Inner Join, Left Join, Right Join, Full Join, Self Join, Cross Join

•       Window Functions

•       Stored Procedures

•       Triggers

•       Common Table Expressions

•       Creating Views and Indexes.

C:  Data Analytics using Excel

•       Understanding Excel

•       Downloading and Installing Excel

•       Operators and Functions in Excel

•       Formatting Data in Excel

•       Importing Data in Excel

•       Data Cleaning in Excel

•       Handling Missing Values

•       LOOKUPs in Excel

•       Pivot Table in Excel

•       Data Modeling in Excel

•       Data Analysis in Excel

•       Making Charts in Excel

•       Understanding Power Query

•       Transforming Data in Power Query

 D: DATA VISUALIZATION USING POWER BI

•       Understanding Power BI

•       Downloading and Installing Power BI

•       Basic Functionalities of Power BI

•       Making Charts in Power BI

•       Power BI Operators and Functions

•       Data Cleaning in Power BI

•       Data Transformations using Power Query

•       DAX Functions in Power BI

•       Data Modelling in Power BI

•       Visualizing Data using Power BI

•       Making Reports and Dashboards in Power BI

•       Understanding Power BI Service

•       Using Power BI Service

2: Python

A: INTRODUCTION TO PYTHON

•       History & Features of Python

•       Versions of Python

•       Applications of Python

•       Scripting vs Programming Language

•       Interactive Mode vs Script Mode

•       Installing Python

•       Writing First Python Program

•       Executing First Python Program using Interactive Mode

•       Executing First Python Program using Script Mode

·        Assignments

·        Getting Started with Python

•       Using print() Function to print Messages

•       Comments

•       Keywords and Identifiers

•       Data Types

•       Variables

•       Using print() Function to print Data

•       Python Operators

•       Type Casting

•       Receiving Input from Keyboard

•       Working with input() Function

·        Assignments

B: DECISION MAKING STATEMENTS

•       If Statement

•       If - else Statement

•       Elif Statement

•       Nested Decision Making Statement

·        Assignments

C: LOOP STATEMENTS

•       For Loop Statement

•       While Loop Statement

•       Break, continue and pass Statements

•       Else with Loop Statement

•       Nested Loops Statement

D: PYTHON COLLECTION TYPES

      i.           Strings

•       Creating Strings

•       Indexing and Slicing in Strings

•       String Operators and Functions

•       String Methods

·        Assignments

    ii.           List

•       Creating Lists

•       List Operators and Functions

•       Indexing and Slicing in List

•       List Methods

•       Converting String into List

•       Converting List into String

•       Nested Lists

·        Assignments

 iii.           Tuples

•       Creating Tuple

•       Functions and Operators on Tuple

•       Indexing and Slicing in Tuple

•       Tuple Methods

•       Nested Tuples

•       Converting String and List to Tuple

•       Converting Tuple to String and List

·        ASSIGNMENTS

  iv.           Dictionary

•       Creating Dictionary

•       Adding and Deleting Keys and Value Pairs

•       Looping through Dictionary

•       Extracting only Keys and only Values from Dictionary

•       Creating Dictionary from List and Tuple

·        Assignments

    v.           Set

•       Creating a Set

•       Add, Removing and Discarding elements to Set

•       Converting String, List and Tuple to Set

•       Converting Set into String, List and Tuple

·        Assignments

E: FUNCTIONS

•       Defining a Function

•       Calling a Function

•       Types of Functions

•       Formal and Actual Arguments

•       Named and Keyword arguments

•       Default and Positional Arguments

•       *args and **kwargs Arguments

•       Local and Global Variables

•       Anonymous Function

·        Assignments

F: MODULES PROGRAMMING

•       Understanding Modules and Packages

•       Creating a Module and Importing the Module

•       Different ways of Importing Modules

•       Working with Built-in Modules like math, sys, os, random, datetime etc.

·        Assignments

G: EXPLORATORY DATA ANALYSIS (EDA) USING PYTHON LIBRARIES

•       Introduction to Python Libraries for Exploratory Data Analysis (EDA)

•       Introduction to Jupyter Notebook

•       Downloading and Installing Anaconda

•       Writing and Executing First Python Program in Jupyter Notebook

•       Using Code Mode, Markdown Mode and Raw Mode of Jupyter Notebook

H: NUMPY LIBRARY

•       What is NumPy Library?

•       Understanding Need of NumPy Library

•       What is a NumPy Array?

•       Types of NumPy Arrays

•       Creating NumPy Arrays

•       Working with NumPy Array Properties

•       Indexing and Slicing in NumPy Arrays

•       Arithmetical Operations on NumPy Arrays

•       Scalar Operations on NumPy Arrays

•       Relational Operations on NumPy Arrays

•       Logical Operations on NumPy Arrays

•       Aggregation Functions on NumPy Array

•       Filtering Functions on NumPy Array

·        Project Work

i: Pandas Library

•       What are Pandas?

•       Types of Pandas Data Structures

•       Creating Series

•       Creating Data Frame

•       Indexing and Slicing in Series

•       Indexing and Slicing in Data Frame

•       Adding New Rows and Columns in Data Frame

•       Removing Existing Rows and Columns in Data Frame

•       Finding Missing Values in Data Frame

•       Replacing and Removing Missing Values in Data Frame

•       Reading Data from CSV File into Data Frame

•       Writing Data to CSV File from Data Frame

•       Exploratory Data Analysis (EDA) using Pandas Library

·        Project Work

J: MATPLOTLIB LIBRARY

•       What is Data Visualization?

•       Understanding Need of Data Visualization

•       What is Matplotlib?

•       Plotting Line Plots using Matplotlib

•       Plotting Bar Plots using Matplotlib

•       Plotting Histograms using Matplotlib

•       Plotting Pie Charts using Matplotlib

•       Customizing Plots using Matplotlib

·        Project Work

K: SEABORN LIBRARY

•       What is the Seaborn Library?

•       Comparison of Matplotlib and Seaborn Libraries

•       Plotting Line Plots using Seaborn

•       Plotting Bar Plots using Seaborn

•       Plotting Histograms using Seaborn

•       Customizing Plots using Seaborn

•       Plotting Distribution Plots using Seaborn

•       Plotting Categorical Plots using Seaborn

Practical Projects & Assessment

·        Real-World Project

·        Quiz + Practical Assignment

·        Final Assessment & Certification