Data Science with Python Certification​

Module 1:- Installing & Running Python

• Python 2.7 vs Python 3
• Local Environment Setup
• Installing Python on different platforms(Windows and Linux)
• Python Interpreter and Python Interactive Shell
• Python IDE(Pydev, Pycharm,VIM)

Module 2:- Python Introduction

• Python Overview
• History Of Python
• CPython, Jython, PyPy
• Python Features
• Areas Of Application of Python
• Understanding More About Python
• Writing your First Python Program
• Interactive Mode Programming
• Script Mode Programming
• Dir and help: Getting help from the Python interpreter.

Module 3:- Python Syntax ,Keywords and Operators

• Python Identifiers
• Various Operators and Operators Precedence
• Reserved Words,Lines and Indentation
• Multi-Line Statements,Quotation in Python
• Comments in Python,Using Blank Lines
• Command Line Arguments
• Python Input/Output:Using the Print Function
• Getting Input from User
• Python Basic Data Types And Variables
• Binary, octal and hexadecimal numbers
• Convert one data type to another

Module 4:- Expressions, Statements, Variables, Strings

• Working With Numbers
• Working With Booleans
• Math library and its various operations
• Working with Strings
• String types and formatting
• String Operations and Task
• Program to find duplicate characters in a String.
• Program to reverse a string
• Program to check if String is Palindrome
• Program to remove a newline in Python

Module 5:- Python Data Types: List,Tuples,Dictionaries

• Python Lists, Tuples, Dictionaries
• Accessing Values
• Basic Operations
• Indexing, Slicing, and Matrixes
• Built-in Functions & Methods
• Exercises on List, Tuples And Dictionary
• Remove Duplicate from Lists
• Program to find the index of an item of a tuple
• Python program to convert a list to a tuple
• Python program to reverse a tuple
• Program to convert a tuple to a dictionary

Module 6:- Making Decisions – if Statements

• The Relational Operators
• The Logical Operators
• Simple if Statement,if-else Statement
• If-elif Statement
• More Advanced If, ElIf & Else Processing

Module 7:- Loop Control

• Introduction To while Loops
• Count-Controlled while Loops
• Event-Controlled while Loops
• Using continuE,Using break
• Introduction To for Loops
• For loops with files,list,tuples and dictionaries

Module 8:- Iterators

• Understanding Iterators
• Using iter And next
• Iterators And Dictionaries
• Other Iterators

Module 9:- Functions And Scopes

• Introduction To Functions – Why
• Defining Functions
• Calling Functions
• Functions With Multiple Arguments
• Predicate Functions,Recursive Functions
• Function Objects,Generators,Decorators
• Anonymous Functions, Higher-Order Functions
• Scope , Global Scope, Local Scope , Nested Scope

Module 10:- Modules and Packages

• Using Built-In Modules
• User-Defined Modules
• Module Namespaces
• Installing and Uninstalling a package
• Package vs Library vs Module

Module 11:- File I/O

• Printing to the Screen
• Reading Keyboard Input
• Opening and Closing Files
• Open Function,file Object Attributes
• close() Method ,Read,write,seek
• Rename,remove,
• Mkdir,chdir,rmdir

Module 12:- Error And Exceptional Handling

• Exception Handling, Assertions: The assert Statement
• What is Exception, Handling an exception
• The except Clause with No Exceptions, the try-finally Clause
• The argument of an Exception, Raising an Exceptions
• User-Defined Exceptions 

Module 13:- Regular Expression

• Matching and Searching- match() and search() Functions
• Search and Replace
• Regular Expression Modifiers
• Regular Expression Patterns
• Regular Expression Quantifiers

Module 14:- Introduction to Data Science and Machine Learning

• Matching and Searching- match() and search() Functions
• Search and Replace
• Regular Expression Modifiers
• Regular Expression Patterns
• Regular Expression Quantifiers

Module 15:- Tools & Languages available

• Python .R
• Python & R Differences
• Python Distribution
• Python tools for Data Science
• Anaconda Installation
• Jupiter Notebook Usage and Examples

Module 16:- Numpy

• Introduction to Numpy. Array
• Creation,Printing Arrays
• Basic Operations- Indexing, Slicing and Iterating
• Shape Manipulation – Changing
• Shape,stacking and spliting of array
• Random number

Module 17:- Pandas, Matplotlib and Seaborn

Pandas

• Introduction to Pandas
• Importing data into Python
• Pandas Data Frames,Indexing Data
• Frames ,Basic Operations With Data
• frame,Renaming Columns,Subletting and filtering a data frame.

Matpolib

• Introduction,plot(),Controlling Line
• Properties,Working with Multiple
• scatter, hist, bar, piechart
• subplot, titles, axis, colormap
• Figures,Histograms

Seaborn

• Plot for categorical and numerical data
• Plot for categorical vs numerical, numerical vs numerical, categorical vs categorical
• distplot, jointplot, boxplot, barplot, countplot, violinplot, swarmplot

Module 18:- Exploratory Data Analysis

• Data Manipulations and Wrangling
• Drawing Insights and Completing analysis
• Imputing NA values