Python Online Training

Python Online Training

Python-online-training-nareshit

About Python Online Training

Python is a Scripting language. It is an interpreted, interactive programming language. It supports the object-oriented concept. Python is an open source.  It has the simple structure with clear define syntax. It is easy to learn. It supports multiple programming paradigms. Python has the large collection of pre-built and portable functionalities. Python is having more than 20 thousand modules. In most of the technologies, Python is being used.  It has a very good feature like automatic memory management system.

Course Objectives

What are the Course Objectives?

After completion of the python Course at Naresh I technologies, you will be expertise and eligible for:

  • Complete knowledge on Python
  • Learn how to use lists, tuples, loops, decision statement, etc. in python
  • Build packages in Python
  • Working with Exception handling, Inheritance
  • Work independently in Project with scripting and Automation

Who should go for this Course?

  • Any IT experienced Professional who are interested to build their career in python web development/ software automation /Data Analytics.
  • Any B.E/ B.Tech/ BSC/ MCA/ M.Sc Computers/ M.Tech/ BCA/ BCom College Students in any stream.
  • Fresh Graduates.

Pre-requisites:

The course can learn by any IT professional having basic knowledge of:

  • Unix or Windows Operating System
  • Any Programming Language

Course Curriculum

  • Python Overview
  • About Interpreted Languages
  • Advantages/Disadvantages of Python pydoc
  • Starting Python
  • Interpreter PATH
  • Using the Interpreter
  • Running a Python Script
  • Python Scripts on UNIX/Windows
  • Python Editors and IDEs.
  • Using Variables
  • Keywords
  • Strings Different Literals
  • Math Operators and Expressions
  • Writing to the Screen
  • String Formatting
  • Command Line Parameters and Flow Control
  • Built-in Functions
  • Lists
  • Tuples
  • Indexing and Slicing
  • Iterating through a Sequence
  • Functions for all Sequences
  • Using Enumerate()
  • Operators and Keywords for Sequences
  • Dictionaries and Sets
  • The xrange() function
  • List Comprehensions
  • Generator Expressions
  • Functions
  • Function Parameters
  • Global Variables
  • Variable Scope and Returning Values. Sorting
  • Alternate Keys
  • Lambda Functions
  • Sorting Collections of Collections
  • Sorting Dictionaries
  • Sorting Lists in Place
  • Errors and Exception Handling
  • Handling Multiple Exceptions
  • The Standard Exception Hierarchy
  • Using Modules
  • The Import Statement
  • Module Search Path
  • Package Installation Ways
  • The Sys Module
  • Interpreter Information
  • STDIO
  • Launching External Programs
  • Paths Directories and Filenames
  • Walking Directory Trees
  • Math Function
  • Random Numbers
  • Dates and Times
  • Zipped Archives
  • Introduction to Python Classes
  • Defining Classes
  • Initializers
  • Instance Methods
  • Properties
  • Class Methods and DataStatic Methods
  • Private Methods and Inheritance
  • Module Aliases and Regular Expressions.
  • Debugging
  • Dealing with Errors
  • Using Unit Tests
  • Project Skeleton
  • Required Packages
  • Creating the Skeleton
  • Project Directory
  • Final Directory Structure
  • Testing your Setup
  • Using the Skeleton
  • Creating a Database with SQLite 3
  • CRUD Operations
  • Creating a Database Object
  • Introduction to Machine Learning
  • Areas of Implementation of Machine Learning
  • Why Python
  • Major Classes of Learning Algorithms
  • Supervised vs Unsupervised Learning
  • Learning NumPy
  • Learning Scipy
  • Basic plotting using Matplotlib
  • Machine Learning application
  • Classification Problem
  • Classifying with k-Nearest Neighbours (kNN)
  • Algorithm
  • General Approach to kNN
  • Building the Classifier from Scratch
  • Testing the Classifier
  • Measuring the Performance of the Classifier
  • lustering Problem
  • Introduction to Scikit-Learn
  • Inbuilt Algorithms for Use
  • What is Hadoop and why it is popular
  • Distributed Computation and Functional Programming
  • Understanding MapReduce Framework Sample
  • Map Reduce Job Run
  • PIG and HIVE Basics
  • Streaming Feature in Hadoop
  • Map Reduce Job Run using Python
  • Writing a PIG UDF in Python
  • Writing a HIVE UDF in Python
  • Pydoop and MRjob Basics
  • Real World Project


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Training Features

Instructor-Led Training Sessions

We believe to provide our students the Best interactive experience as part of their learning

Expert Trainers

We Constantly evaluate our trainers and only the “Best” Provides the Training

Flexible Schedule

Do not hesitate to ask… because we will work according to your calendar

Industry Specific Scenarios

Students are provided with all the Real-Time and Relevant Scenarios

e-Learning Sessions

Online training sessions are held Live and we provide students with the Training Videos

24/7 Support

No [email protected] all…!!! Your Question will be answered by Us at any Hour of the time

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