Python Training

• Python Modes of Execution
• Interactive mode of Execution
• Batch mode of Execution
• Python Editors and IDEs
• Python Data Types
• Python Constants
• Python Variables
• Comments in Python
• Flavors of Python
• Input() Function: Accepting input
• Type Conversion
• Type(), Id() Functions
• Comments in Pythont
• Escape Sequences in Python
• Strings in Python
• String indices and slicing

• Arithmetic Operators
• Comparison Operators
• Logical Operators
• Assignment Operators
• Short Hand Assignment Operators
• Bitwise Operators
• Membership Operators
• Identity Operators

• Pycharm IDE Installation
• Working with Pycharm
• Pycharm components
• Installing Anaconda
• What is Conda?
• Anaconda Prompt
• Anaconda Navigator
• Jupyter Notebook
• Jupyter Features
• Spyder IDE
• Spyder Features
• Conda and PIP

• Block/clause
• Indentation in Python
• 1.Conditional Statements
1. if stmt
2. if…else statement
3. if…elif…statement

• while loop
• while else
• for loop
• Range() in for loop
• Nested for loop
• Break statement
• Continue statement
• Pass statementt

• Creating Strings
• String indexing
• String slicing
• String Concatenation
• String Comparison
• String splitting and joining
• Finding Sub Strings
• String Case Change
• Split strings
• String methods

• Introduction
• Lists
• Tuples
• Sets
• Dictionaries
• Operations on collections
• Functions for collections
• Methods of collection
• Nested collections
• Differences b/w list tuple and set and Dictionary

• List properties
• List Creation
• List indexing and slicing
• List Operations
• Nested Lists
• List modification
• List insertion and deletion
• List Methods

• Tuple properties
• Tuple Creation
• Tuple indexing and slicing
• Tuple Operations
• Nested Tuples
• Tuple Methods
• Differences b/w List and Tuple

• Set properties
• Set Creation
• Set Operations
• Set Mathematical Operations
• Set Methods
• Insertion and Deletion operation

• Dictionary properties
• Dictionary Creation
• Dictionary Operations
• Dictionary Methods
• Insertion and Deletion of elements
• Differences b/w list tuple and set and Dictionary

• Defining a function
• Calling a function
• Properties of Function
• Examples of Functions
• Categories of Functions
• Argument types
1. default arguments
2. non-default arguments
3. keyword arguments
4. non-keyword arguments
• Variable Length Arguments
• Variables scope
• Call by value and Call by Reference
• Passing collections to function
• Local and Global variables
• Recursive Function
• Boolean Function
• Passing functions to function
• Anonymous or Lambda function
• Filter() and map() functions

• What is a module?
• Different types of module
• Creating user-defined module
• Setting path
• The import statement
• Normal Import
• From ... Import
• Module Aliases
• Dir function
• Working with Standard modules - Math, Random, Date time and os modules

• Introduction to packages
• Defining packages
• Importing from packages
• __init__.py file
• Defining sub-packages
• Importing from sub-packages

• Types of errors
• Compile-Time Errors
• Run-Time Errors
• What is Exception?
• Need of Exception handling
• Predefined Exceptions
• Try, Except, finally blocks
• Nested blocks
• Handling Multiple Exceptions
• User-defined Exceptions
• Raise statement

• Introduction
• Types of Files
• Opening a file in Python
• Closing a file
• Writing data to files
• Tell() and seek() methods
• Reading data from files
• Appending data to files
• With open stmt
• Various functions

• OOPS Features
• Encapsulation
• Abstraction
• Class
• Object
• Static and non-static variables
• Defining methods
• Diff b/w functions & methods
• Constructors
• Parameterized Constructors
• Built-in attributes
• Object Reference count
• Destructor
• Garbage Collection
• Inheritance
• Types of Inheritances
• Polymorphism
• Overriding
• Super() statement

• What is regular expression? Special characters
• Forming regular expression
• Compiling regular expressions
• Grouping
• Match() function
• Search() function
• Matching vs searching
• Splitting a string
• Replacing text
• Validations

• Introduction
• Installing Oracle database
• Creating database users, Installing Oracle Python modules
• Establishing connection with Oracle
• Closing database connections
• Cursor object
• Executing SQL queries
• Retrieving data from Database
• Using bind variables executing
• SQL queries
• Transaction Management
• Handling errors

• How to Use Date & DateTime Class
• Time and date Objects
• Calendar in Python
• The Time Module
• Python Calendar Module

• Introduction
• getcwd
• listdir
• chdir
• chdir
• mkdir
• rename file/dir
• remove file/dir
• Os help
• Os operations

• Python Iterator
• Python Generator
• Python closure
• Python Decorators
• Web scraping
• PIP
• Working with CSV files
• Working with XML files
• Working with JSON files
• Debugging

• Introduction
• Components and events
• Root window
• Fonts and colors
• Buttons, checkbox
• Label widget
• Message widget
• Text widget
• Image

• Introduction
• Pandas module
• Numpy module
• Matplotlib module
• Working Examples

• Installing and working with Xlsx writer
• Creating Excel Workbook
• Inserting into Excel sheet
• Inserting data into multiple Excel sheets
• Creating headers
• Installing and working with xlrd module
• Reading a specific cell or row or column
• Reading specific rows and columns

Yes, Python is a great career choice due to its high demand, versatility, and strong salary potential in fields like software development, data science, and AI. Its ease of learning and vast job opportunities make it a future-proof skill.

Python has a vast scope across multiple industries, including web development, data science, artificial intelligence, cybersecurity, automation, and cloud computing. Its versatility, ease of use, and strong community support make it a future-proof language with growing job opportunities worldwide.

Yes, starting your career with Python is a great idea! It offers high demand, diverse career paths (software development, data science, AI, automation, etc.), and competitive salaries. Its beginner-friendly syntax and strong community support make learning and career growth easier.

Before learning Python, it's helpful to have basic problem-solving skills, logical thinking, and a fundamental understanding of computers. Familiarity with basic math concepts can also be useful for certain applications like data science.

• Basics of Python.
• The basics of Python include understanding syntax, variables, data types, control flow (if/else, loops), functions, and error handling. Python also allows using external libraries to extend functionality for various applications.

Python is ideal for web development due to its simple syntax, readability, and scalability. Popular frameworks like Django and Flask speed up development, while Python's large library ecosystem and integration capabilities allow easy handling of databases, APIs, and more.

Python's object-oriented programming (OOP) features, like classes and inheritance, help organize code, making it more modular, reusable, and easier to maintain. This structure is key for building scalable applications that can grow and adapt over time.

Yes, Python has a bright future due to its versatility, ease of use, and widespread adoption in fields like data science, AI, web development, and automation. Its large community, continuous updates, and growing demand in various industries ensure its relevance for years to come.

Mastering Python typically takes anywhere from 6 months to 8 months, depending on your prior programming knowledge and how much time you dedicate. Continuous practice and real-world projects are key to truly mastering the language.

Python offers high demand across diverse fields like data science, AI, and web development, along with competitive salaries. Its simplicity, versatility, and vast community support make it a valuable career choice with long-term growth potential.

Anyone willing to learn can take the course of Pythpon Course: below are the educational background candidates can easily opt for it.

• Engineers
• Marketing Professionals
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