Python Training

Python is a powerful, flexible, open source language that is easy to learn, easy to use, and has powerful libraries for Data manipulation and Data Analysis.
Python has a unique combination of being both a capable general-purpose programming language as well as being easy to use for Analytical and Quantitative computing. For over a decade, Python has been used in scientific computing and highly quantitative domains. At the same time, Python has been used to build massively scalable web applications. The other important side of python is its ability to integrate easily with web applications.
Python is becoming very popular option for Big Data Processing due to its simple usage and wide set of data processing libraries. Python is easy for Big Data Analysts to learn and use, but powerful enough to tackle even the most difficult problems in virtually any domain. It integrates well with existing IT infrastructure, and is platform independent.
All the above mentioned features of Python are making it a popular choice for Big Data Analytics. In the current era of Big Data, Python is getting more popularity and the demand for Python professionals is ever increasing than before.

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What you will learn?

This course provides students with comprehensive understanding of Python programming language in general. Students can then utilize this knowledge by using Python in areas like Web and Internet development (HTML, XML, JSON parsing, scripting, email processing), creating Desktop applications, GUI programming, Rapid prototyping, Gaming, image processing, robotics, Numeric and scientific computing, Data Analytics and Machine learning.

Who can attend?

IT Beginners/ Freshers/ Developers/ Data Analysts/ Data Scientists

Suggested Pre-requisites for Python Training

This is a starter course and hence no specific prerequisites required. However basic knowledge of any programming language would be advantageous. Basic computer operating knowledge is desirable.

Training Highlights

  • Training covers Python 2.x and 3.x versions.
  • Extensive syllabus, compared to any other institute
  • Top Quality course material for self-study and future reference
  • In-depth coverage with real world examples and scenarios
  • Dedicated System for practice
  • 100% Placement assistance by full-fledged in-house placement cell
  • 100% satisfaction guaranteed
1. Introduction

  • What is Python?
  • Why do people use Python?
  • Who uses Python today?
  • What can I do with Python?
  • How is Python developed and supported?
  • Features of Python
2. Running a Python Program

  • The Python Interpreter
  • The Python IDEs
  • Python implementation alternatives
3. Type & Operators

  • Introducing Core Data Types
  • Numbers and Strings
  • Lists and Sets
  • Dictionary and Tuples
  • Files
  • Other core types and operators
4. Statements

  • Assignments and Expressions
  • The if statement
  • The if/else ternary expression
  • The while and for loops
  • Iterations and comprehensions
5. Functions

  • Why use Functions?
  • Function definition and calls
  • Python scopes
  • The LEGB rule
  • The global statement
  • Scopes and nested functions
  • Closures: The factory functions
  • The non-local statement
6. Arguments

  • Passing arguments to Function
  • Keyword and Default arguments
  • Keyword only arguments
  • Writing your own print function
7. Advanced Function Topics

  • Recursive Functions Anonymous
  • Functions: lambdas
  • Functional programming tools: map, filter and reduce
8. Comprehensions and Generators

  • List Comprehensions
  • Generator functions
  • Generator expressions Scopes and comprehensions variables
  • Set and Dictionary comprehensions
9. Benchmarking

  • Timing iteration alternatives
  • Writing your own timing module
  • Timing module alternatives
10. Modules

  • Why modules?
  • Python program architecture
  • How import works
  • Module search path
  • Creating modules
  • Using modules
  • Module namespaces
  • Reloading modules
11. Packages

  • Introduction to package
  • Why use package imports?
  • Package relative imports
  • Pitfalls of package relative imports
  • Namespaces packages
12. Advanced Module concepts

  • Data hiding in modules
  • Understanding __main__ and __name__
  • Changing the module search path
  • Using as with import and from
  • Importing modules by Name String
  • Exposing the Modules further
13. Classes and OOPS

  • Overview of OOP
  • Creating classes
  • Creating Instance Objects
  • Accessing attributes
  • Built-in class attributes
  • Method calls
  • Abstract super classes
  • Nested classes
14. Operator Overloading

  • Introduction
  • Indexing and slicing: __getitem__ and __setitem__
  • Iterable objects: __iter__ and __next__
  • Membership:__contains__,__iter__ and __getitem__
  • Attribute access: __getattr__ and __setattr__
  • String representation: __str__ and __repr__
  • Right side and in-place uses: __radd__ and __iadd__
  • Overloading comparasion operators
  • Boolean tests: __bool__ and __len__
  • Call expression: __call__
  • Object destruction: __del__
15. Advanced class topics

  • Containership
  • The 'New Style' class model
  • Static and class methods
  • Instance count with static methods
  • Instance count with class methods
  • The 'Super' function
16. Exception Handling

  • What is an Exception?
  • Handling an Exception
  • The try, except and else blocks
  • Except clause with no exception
  • Except clause with multiple exceptions
  • The try-finally clause
  • Argument of an exception
  • Raising an exception
  • User defined exceptions
  • Built-in exception classes
17. Unicode and Byte Strings

  • Strings and Unicode Strings
  • Byte and Bytearray objects
  • Text and Binary files
  • Unicode files
  • Pattern matching with re
  • Binary data module "struct"
  • Serializing objects with Pickle
  • XML parsing
18. Decorators

  • What is a decorator?
  • Function decorators
  • Class decorators
19. Metaclasses

  • What is a Metaclass?
  • The Metaclass model
  • Declaring Metaclasses
  • Coding Metaclasses
  • Metaclass Vs Superclass
  • Metaclass methods Vs Class methods

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  • Well structured Training Material for future reference
  • Training on Latest Versions – Oracle 12c
  • Individual attention and group discussions for Interview preparation
  • Dedicated systems for Lab practice supported by qualified Lab Administrators and UPS for power backup
  • Unlimited Lab Access till you get job

Uclid has best of the best teaching faculties who are real time IT Professionals working with top MNCs. Each faculty has a minimum 10 years of real time experience in Programming and working in the capacity of project leaders and project managers in various MNCs. You will benefit from their rich experience by going through the real time scenarios and case studies during the training. At the end of the course you will not only learn PYTHON but familiarize yourself with the real time aspects of PYTHON.