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Python Online Training

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About Python Online Training

Python online training: The use of big data and cloud computing solutions in the enterprise world has helped skyrocket Python to success. It is one of the most popular languages used in data science, second only to R. It’s also being used for machine learning and AI systems and various modern technologies.

Python online training is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java. It is an easy-to-use language that makes it simple to get your program working. This makes Python ideal for prototype development and other ad-hoc programming tasks, without compromising maintainability.

Comes with a large standard library that supports many common programming tasks such as connecting to web servers, searching text with regular expressions, reading and modifying files. Python’s interactive mode makes it easy to test short snippets of code. There’s also a bundled development environment called IDLE. It is easily extended by adding new modules implemented in a compiled language such as C or C++. Can also be embedded into an application to provide a programmable interface.

About the Trainer:

Anusha K has about 7.5+ years of experience working in IT across different domains and with multiple CMM Level 5 companies. Has hands on experience working on end-to-end development and training as well.

Course Information
Hours 35 hours
Duration 6 weeks [6 days per week]
Slot 6:30AM-7:30AM IST
Mode LIVE Online Training
Join Goto Meeting
Demo Day-1 & Day2
Downloads Recordings, Materials, Workspace, Applications etc
Price 7,500 INR

====================Course Curriculum=================

  • Python Introduction
  • Using the Python Interpreter
    • Invoking the Interpreter
      • Argument Passing
      • Interactive Mode
    • The Interpreter and Its Environment
      • Source Code Encoding
  • Programming in python
    • Using Python as a Calculator to understand:
      • Numbers
      • Strings
      • Lists
    • Basic Programming
  • More Control Flow Tools
    • if Statements
    • for Statements
    • The range() Function
    • break and continue Statements, and else Clauses on Loops
    • pass Statements
    • Defining Functions
    • More on Defining Functions
      • Default Argument Values
      • Keyword Arguments
      • Arbitrary Argument Lists
      • Unpacking Argument Lists
      • Lambda Expressions
      • Documentation Strings
      • Function Annotations
    • Intermezzo: Coding Style
  • Data Structures
    • More on Lists
      • Using Lists as Stacks
      • Using Lists as Queues
      • List Comprehensions
      • Nested List Comprehensions
    • The del statement
    • Tuples and Sequences
    • Sets
    • Dictionaries
    • Looping Techniques
    • More on Conditions
    • Comparing Sequences and Other Types
  • Modules
    • More on Modules
      • Executing modules as scripts
      • The Module Search Path
      • “Compiled” Python files
    • Standard Modules
    • The dir() Function
    • Packages
      • Importing * From a Package
      • Intra-package References
      • Packages in Multiple Directories
  • Input and Output
    • Fancier Output Formatting
      • Formatted String Literals
      • The String format() Method
      • Manual String Formatting
      • Old string formatting
    • Reading and Writing Files
      • Methods of File Objects
      • Saving structured data with json
  • Errors and Exceptions
    • Syntax Errors
    • Exceptions
    • Handling Exceptions
    • Raising Exceptions
    • User-defined Exceptions
    • Defining Clean-up Actions
    • Predefined Clean-up Actions
  • Classes
    • A Word About Names and Objects
    • Python Scopes and Namespaces
      • Scopes and Namespaces Example
    • A First Look at Classes
      • Class Definition Syntax
      • Class Objects
      • Instance Objects
      • Method Objects
      • Class and Instance Variables
    • Random Remarks
    • Inheritance
      • Multiple Inheritance
    • Private Variables
    • Odds and Ends
    • Iterators
    • Generators
    • Generator Expressions
  • Standard Python Library
    • Operating System Interface
    • File Wildcards
    • Command Line Arguments
    • Error Output Redirection and Program Termination
    • String Pattern Matching
    • Mathematics
    • Internet Access
    • Dates and Times
    • Data Compression
    • Performance Measurement
    • Quality Control
    • Batteries Included
  • Advanced Python Libraries
    • Output Formatting
    • Templating
    • Working with Binary Data Record Layouts
    • Multi-threading
    • Logging
    • Tools for Working with Lists
    • Decimal Floating point Arithmetic
  • Virtual Environments and Packages
    • Introduction
    • Creating Virtual Environments
    • Managing Packages with pip
  • Interactive Input Editing and History Substitution
    • Tab Completion and History Editing
    • Alternatives to the Interactive Interpreter
  • Floating Point Arithmetic: Issues and Limitations
    • Representation Error
  • Interactive Mode
    • Error Handling
    • Executable Python Scripts
    • The Interactive Startup File
    • The Customization Modules

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