Python Programming and Machine Learning

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About the Course:

Python is powerful and fast; plays well with others; runs everywhere; is friendly & easy to learn; is open. Python is a programming language that lets you work more quickly and integrate your systems more effectively.

Python is an interpreted, interactive, object-oriented programming language. It incorporates modules, exceptions, dynamic typing, very high level dynamic data types, and classes. Python combines remarkable power with very clear syntax. It has interfaces to many system calls and libraries, as well as to various window systems, and is extensible in C or C++. It is also usable as an extension language for applications that need a programmable interface. Finally, Python is portable: it runs on many UNIX variants, on the Mac, and on PCs under MS-DOS, Windows, Windows NT, and OS/2.

Python is a one-stop shop. There is a Python framework for pretty much anything, from web apps to data analysis. Python is often heralded as the easiest programming language to learn, with its simple and straightforward syntax. Python has risen in popularity due to Google’s investment in it over the past decade.

Why Python?

  • Provides an opportunity for you to upskill
  • Enhances programming knowledge portfolio
  • Improves your employability quotient
  • Increases your chances of getting into Big Data & Bio Informatics
  • Widely used in Bioinformatics applications
  • Engineers use Python to make scientific calculations, design systems, and simulation software
  • System administrators as they are increasingly replacing their shell scripts with Python scripts


Course Details

  • History, features and Installation
  • Introduction
    • Keywords and Identifiers
    • Statements and comments
    • Input, Output and Import
    • Python operators
  • Variables, expression
  • Conditionals
  • Functions
  • Flow control
    • Python if…else
    • For loop
    • While loop
    • Break and continue
    • Pass statement
  • Native Data types
    • Python numbers
    • Python list
    • Tuple
    • String
    • Set
    • Dictionary
    • Conversion between data types
  • String operations
  • Files
  • Modules and Packages
  • Object and Class
  • Web scraping
  • Numerical Python (Numpy)
  • Pandas for high-level data manipulation
  • Data visualization using Matplotlib and ggplot (examples and case studies)
  • Descriptive statistics and analytics using Python (examples and case studies)
  • Machine learning using Python (examples and case studies)
    • Unsupervised-Cluster analysis
    • Supervised- Decision Tree
  • Project work

Program Highlights

  • In-depth teaching
    • On Python programming using built-in and user-defined functions
    • Data Visualization & Analytics
    • Machine Learning
  • Project
    • Project work on Machine Learning in Telecom / Retail / Financial Services sector



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