Overview

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Python training program designed by NetLabs ITS is to help you master this hugely sought-after programming language with ease & perfection. Python is an extensively used high-level programming language for general-purpose programming. Python consists of a lot of modules and packages which support modularity of the code and help to increase the application performance. It aids manifold programming paradigm which offers automatic programming management.

Our Python training program covers every module and helps you to gain knowledge with the clear understanding. Our well planned training course ensures to get you equipped with the thorough knowledge of latest concepts and relevant industry topics under the guidance of our proficient & well experienced faculties.

Candidates applying for Python training must have a working knowledge of at least one other programming language along with an experience of working with operating systems like Linux, Windows, Mac OS or Solaris.

Target Audience :

While any graduate or IT professional can go for Python training, it is better suited for software engineers and developers, programmers and webmasters looking to learn a new language and master Python for better career opportunities. Also, those with an interest to explore new programming languages will grasp the contents of the course easily and pave the way for a successful career ahead.

Duration  - 48 Hours (Weekend Classroom sessions ; 4 Hours per session)

• Python Fundamentals
• Data Handling
• String Manipulation
• List Manipulation
• Program Control Flow
• Functions
• Modules & Packages
• Classes & Objects
• Introduction to Oops
• Turtle Programming
• Multi Threding
• Exception Handling
• Advanced Concepts

• Build, develop and debug Python programs
• Implement the programming language on given scenario
• Smartly use Python functions to simplify tasks at work
• Build your own or import modules from the Python standard library
• Write proper codes for input-output data management
• Use expressions to search for text, files or directories
• Use data structures