Paython courses in pune ppt
- 2. What is Paython • ETLhive brings a new training course in the widely acclaimed programming language Python, designed primarily for the budding programmers who wish to make it bigin the Data Analytics Domain. This high-level programming language with its powerful library, clear syntax, and high readability has emerged as one of the "must- know"languages.
- 3. Introduction to Python • - Defining Python • - History of Python and its growing popularity • - Features of Python and its wide functionality • - Python 2 vs Python 3 • - Running a Python Script • - Python Scripts on UNIX and Windows • - Installation on Ubuntu-based Machines • - Python Identifiers and Keywords • - Indentation in Python
- 4. Python Data Types • - Objectives • - Variables and their types • - Variables - String Variables • - Variables - Numeric Types • - Variables - Boolean Variables • - Dictionary and Python • - Types of Variables - Dictionary • - Comparision of Variables
- 5. Functions and Error Handling Techniques • - Creating and Calling Functions • - Python user Defined Functions • - Python packages Functions • - Lambda Function • - Loops in Python - While, Nested, Demo-Create • - Statements - Break Statements, Continue Statements • - Python Exceptions Handling and Standard Exception Hierarchy • - try... except...else • - try... finally...clause • - User-defined Exceptions • - Summary • - Conclusion
- 6. Object Oriented Programming in Python • - Overview of Object Oriented Programming • - Defining Classes, Objects, and Initializers • - Attributes - Built-In Class • - Destroying Objects • - Methods - Instance, Class, Static, Private methods, and Inheritance • - Data Hiding • - Module Aliases and reloading modules • - Regular expressions • - Match Function, Search Function, and the Comparision • - Search and Replace • - Wildcard
- 7. Machine Learning with Python• - Defining Machine Learning • - Implementation of Machine Learning • - Machine Learning and Python • - Algorithms • - Learning NumPy and Scipy • - Learning - Supervised or Unsupervised • - Supervised, Unsupervised Learning and Classification • - Classification and k-Nearest Neighbours (kNN) • - Building, Testing, and Measuring the Performance of the Classifier • - Defining Clustering Problem • - k-Means Clustering • - Pandas - Creating and Manipulating Data • - Summary • - Conclusion