This course is a step-by-step tutorial with each section covering a distinct topic enhanced with discussions and examples; the topics have a wide variety ranging from the basics and fundamentals of Python to advanced skills.

In this training you will gain, basic programming practices to high-end tools and techniques that will help you set apart as a successful Python programmer.
1.Introduction
•Introduction
•Python Promo
•Course Structure
•Python Overview

2.Getting Started with Python3
•Introduction
•Installation Python Windows /OSX/Ubuntu
•REPL
•Significant White Spaces in Python
•Python Culture & Zen of Python
•Importing from Python
•Scalar Types : int , float , None & Boolean
•Relational Operators
•Conditional statements
•While Loops
•Summary

3.Strings & collections
•Introduction
•Strings
•Bytes
•List
•Dictionaries
•For-Loops
•All-Together
•Summary

4.Modularity
•Introduction
•Creating, Running & importing Modules
•Defining Functions & returning values
•Distinguishing Between Modules & Module execution
•The Python Execution Model
•Main Functions & Command Line Arguments
•Sparse is better than Dense
•Documenting using Docstrings
•Documenting with Comments
•The Shebang
•Summary

5.Objects
•Introduction
•Argument Passing
•Function Arguments in Detail.
• Pythons Type System.
•Variable Scoping.
•Everything is a Object.
•Summary

6.Collections
•Introduction
•Tuple
•String
•List
•Shallow Copies
•List Repetition
•More on Lists
•Growing, Sorting Lists
•Dictionary
•Set
•Collection Protocols
•Summary

7.Handling Exceptions
•Introduction
•Exceptions & flow Control
•Handling Exceptions
•Programmer Errors
•Imprudent Error Codes
•Re-Raising Exceptions
•Exceptions as APIs
•Exceptions, APIs, and Protocols
•Do Not Guard Against Type Errors
•EAFP vs. LBYL
•Clean-Up Actions
•Platform-Specific Code
•Summary

8.Iterables
•Introduction
•List Comprehensions
•Set Comprehensions
•Dictionary Comprehensions
•Filtering Predicates
•Iteration Protocols
•Generators
•Stateful Generator Functions
•Laziness and the Infinite
•Generator
•Batteries Included for Iteration
•Summary

9.Classes
•Introduction
•Defining Classes
•Instance Methods
•Initializers
•A Second Class
•Collaborating Classes
•Example: Booking Seats
•Defining Implementation Details
•OO With Function Objects
•Polymorphism and Duck Typing
•Inheritance and Implementation Sharing
•Summary

10.Files and Resource Management
•Introduction
•Writing Text Files
•Reading Text Files
•Appending to Text Files
•Files as Iterators
•Managing Files With Try..Finally
•Context Managers and with-blocks
•Simple Is Better Than Complex
•Writing Binary Files
•Bitwise Operators
•Fractal Images
•Reading Binary Files
•File Like Objects
•Closing With Context Managers
•Summary

11.Shipping Working and Maintainable Code
•Introduction and unittest
•Debugging With PDB
•Virtual Environments
•Distributing Your Programs
•Installing Third-Party Modules
•Moment of Zen
•Summary

12.Regular Expressions (regex)
•regex module
•regex search

13.JSON
•json.module
•json.loads
•json.dumps

14.Basics of Machine Learning

Project 1:Email Server Automation Using Python
Project 2:Selenium Testing Automation in Devops Using Python

1.Introduction
•Introduction
•Python Promo
•Course Structure
•Python Overview

2.Getting Started with Python3
•Introduction
•Installation Python Windows /OSX/Ubuntu
•REPL
•Significant White Spaces in Python
•Python Culture & Zen of Python
•Importing from Python
•Scalar Types : int , float , None & Boolean
•Relational Operators
•Conditional statements
•While Loops
•Summary

3.Strings & collections
•Introduction
•Strings
•Bytes
•List
•Dictionaries
•For-Loops
•All-Together
•Summary

4.Modularity
•Introduction
•Creating, Running & importing Modules
•Defining Functions & returning values
•Distinguishing Between Modules & Module execution
•The Python Execution Model
•Main Functions & Command Line Arguments
•Sparse is better than Dense
•Documenting using Docstrings
•Documenting with Comments
•The Shebang
•Summary

5.Objects
•Introduction
•Argument Passing
•Function Arguments in Detail.
• Pythons Type System.
•Variable Scoping.
•Everything is a Object.
•Summary

6.Collections
•Introduction
•Tuple
•String
•List
•Shallow Copies
•List Repetition
•More on Lists
•Growing, Sorting Lists
•Dictionary
•Set
•Collection Protocols
•Summary

7.Handling Exceptions
•Introduction
•Exceptions & flow Control
•Handling Exceptions
•Programmer Errors
•Imprudent Error Codes
•Re-Raising Exceptions
•Exceptions as APIs
•Exceptions, APIs, and Protocols
•Do Not Guard Against Type Errors
•EAFP vs. LBYL
•Clean-Up Actions
•Platform-Specific Code
•Summary

8.Iterables
•Introduction
•List Comprehensions
•Set Comprehensions
•Dictionary Comprehensions
•Filtering Predicates
•Iteration Protocols
•Generators
•Stateful Generator Functions
•Laziness and the Infinite
•Generator
•Batteries Included for Iteration
•Summary

9.Classes
•Introduction
•Defining Classes
•Instance Methods
•Initializers
•A Second Class
•Collaborating Classes
•Example: Booking Seats
•Defining Implementation Details
•OO With Function Objects
•Polymorphism and Duck Typing
•Inheritance and Implementation Sharing
•Summary

10.Files and Resource Management
•Introduction
•Writing Text Files
•Reading Text Files
•Appending to Text Files
•Files as Iterators
•Managing Files With Try..Finally
•Context Managers and with-blocks
•Simple Is Better Than Complex
•Writing Binary Files
•Bitwise Operators
•Fractal Images
•Reading Binary Files
•File Like Objects
•Closing With Context Managers
•Summary

11.Shipping Working and Maintainable Code
•Introduction and unittest
•Debugging With PDB
•Virtual Environments
•Distributing Your Programs
•Installing Third-Party Modules
•Moment of Zen
•Summary

12.Regular Expressions (regex)
•regex module
•regex search

13.JSON
•json.module
•json.loads
•json.dumps

14.Basics of Machine Learning
Project 1: Email Server Automation Using Python
Project 2: Selenium Testing Automation in Devops Using Python

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• Regular classes – 4 weeks
• Weekend Classes – 6 weeks
• Customized Fast Track option is available as well. Call +91-8049202039 now to customize according to your requirement

• Experienced IT professionals
• Having hands on practical knowledge
• With experience of training large batches in both offline and online mode

• Online Self Paced Training (SPT) with Videos and Documents
• Online Instructor Led Training (ILT)

About the course:

Study9 provides a robust job market focused python storage training. Our python course is designed with the right mix of basic and advanced topics to get one started in the domain and enable a person to get a good job in this competitive market. Our python trainers are experienced professionals with hands on knowledge of python projects. The python course content is designed with keeping the current job market’s demands in mind.Our python training course is value for money and tailor made for our students.

About Study9 Training Method

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The Study9 python training courses are completely online training courses. The online python training is given using advanced training softwares to make the students comfortable with the online training. The student and teacher can talk over VOIP software, they can share each others screens, share python course contents and concerns during the class through chat window and even can see each other using Webcams. The time tested proven online python training methodologies adopted by study9 are of the most advanced ones in India. The student will feel at ease with the python training mode. And we are so confident on that, we offer a moneyback if the student is not satisfied with first python Training class.

The cloud based python training course contents are accessible from anywhere in the world. Study9 provides access for each student to an online Learning Management System that holds all the slides and videos that are part of the python training courses. The students can access them from their Laptop, Mobile, Tablets etc. The students will also give python training exams on this Learning Management System and our expert python trainers will rate their papers and provide certifications on successful completion of these python training exams.

The best part of this online python training approach is that it does not require one to waste time by travelling to a particular python training center. And the timings are flexible so that if someday the student has problems in taking the morning python training class he/she can fix an alternate time in the evening in discussion with python trainer. On need basis our python trainers can take a class in late night as well. On request basis missed python training class sessions can even be given as video lectures to the student for them to go through to be prepared for the next class.