Mastering Python Certification Training Course Overview

Python is a general purpose, versatile and popular programming language. It can be used for everything from web development to software development and scientific applications.

This course will be a great introduction to the participants on both fundamental programming concepts and the Python programming language. At the end, participants will be familiar with Python syntax and will be able to put into practice what you have learned in a final project.

Target Audience

  • People who are new to the IT industry
  • Any IT professional

Learning Objectives

  • Upon completion of the course, you will be able to accomplish:
  • Knowledge on how to develop a project using Python
  • Knowing to describe the basics of the Python programming language
  • Using the variables to store, retrieve and calculate information
  • Utilization of the core programming tools such as functions and loops
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Mastering Python (88 Hours) Download Course Contents

Live Virtual Classroom
Group Training 3400
22 Nov - 02 Dec GTR 09:00 AM - 05:00 PM CST
(8 Hours/Day)

06 - 16 Dec 09:00 AM - 05:00 PM CST
(8 Hours/Day)

1-on-1 Training (GTR) 3950
4 Hours
8 Hours
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Weekend

Start Time : At any time

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12 PM

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Course Modules

Module 1: Getting Started with Python
  • Introduction Python
  • Installing Python on Windows
  • Installing Python on Linux and Other Operating Systems
  • Introduction Python IDLE
  • Programming in Interactive Mode
  • Programming in Scripting Mode
Module 2: Types, Variables and Input / Output
  • Using quotes and escape character
  • String Concatenation and Repeater Operators
  • Using Mathematical Operators with Numbers
  • Understanding Variables
  • Getting User Input with input()
  • Using Strings Methods
  • Converting Values
Module 3: Flow Control in Python
  • The if Statement
  • The else Clause
  • Using elif Clause
  • The while Statement
  • Avoiding infinite loops
  • Values as conditions
  • Using Logical Operators
  • Planning Your Program with Pseudocode
Module 4: For & while Loops
  • How to use While
  • How to use While..else
  • Using For
  • Iteration
Module 5: Lists in Python
  • Creating and Using Lists
  • Len() with Lists
  • In Operator with Lists
  • Indexing, Slicing and Concatenating
  • Deleting List Element with del
  • Using Lists Methods such as append(), sort(), reverse(), count(), pop(), remove(), insert() and index()
  • Using Nested Sequences
  • Understanding Shared References
Module 6: Tuple
  • Using Tuples
  • Sequence Operators with Tuple
  • Functions with Tuples
Module 7: Dictionaries
  • Using Dictionaries
  • Accessing Dictionary values
  • Adding, Replacing and Deleting key-value pairs
  • Functions: get(), keys(), values() and items()
Module 8: Functions in Python
  • Defining Functions
  • Using Parameters and Return Values
  • Using Arguments and Defaults Parameters
  • Using Global Variables and Constants
  • Variable Scope
  • References
Module 9: Modules
  • Using Modules in Programs
  • Writing Modules
  • Importing Modules
  • Using Imported Functions and Modules
Module 10: OS Services
  • The os module
  • Environment variables
  • Launching external commands
  • Walking directory trees
  • Paths, directories, and filenames
  • Working with file systems
  • Dates and times
Module 11: File Input and Output and Exception
  • The open Functions
  • Input from Text Files
  • Storing Complex Data in Files with Pickles and Shelve
  • Handling Exceptions
  • Using try Statement with except Clause
  • Handling Multiple Exception
Module 12: XML and JSON Data
  • Working with XML
  • DOM
  • Introducing ElementTree and xml
  • Parsing XML
  • Navigating the document
  • Creating a new XML document
  • JSON
  • Parsing JSON into Python
  • Converting Python into JSON
Module 13: Object Oriented Python
  • Introduction to Object Oriented Python
  • Creating Classes, Methods and Objects
  • Using Constructor and Attributes
  • Using Class Attributes and Static Methods
  • Understanding Encapsulation
  • Private Attribute Access
  • Using Inheritance to Create New Classes
  • Altering Behaviour of Inherited Methods
  • Understanding Polymorphism
Module 14: Metaprogramming
  • Implicit properties
  • globals() and locals()
  • Working with attributes
  • The inspect module
  • Decorators
  • Monkey patching
Module 15: Database access
  • The DB API
  • Available Interfaces
  • Connecting to a server
  • Creating and executing a cursor
  • Fetching data
  • Parameterized statements
  • Metadata
  • Transaction control
  • Other DBMS modules
Module 16: Network Programming
  • Sockets
  • Clients
  • Servers
  • Application protocols
  • Forking servers
  • Binary data
  • The struct module
Module 17: Multiprogramming
  • When to use threads?
  • The Global Interpreter Lock
  • The threading module
  • Simple threading
  • Sharing variables
  • The queue module
  • Debugging threaded programs
  • Multiprocessing
  • Other alternatives
Module 18: Graphical Application Development
  • Examining A GUI
  • Understanding Event Driven Programming
  • Introduction to Tkinter Module
  • Using Root Window
  • Creating Frames
  • Using Labels and Buttons
  • GUI Programs with Classes
  • Binding Widgets and Event Handlers
  • Using Text and Entry Widgets
  • Using the Grid Layout Manager
  • Using Check and Radio Buttons
Module 19: Django Web Framework
  • Features of Django
  • Installation of Django
  • MVC model
  • HTTP concepts
  • Views
Module 20: Templates and Form
  • Django Template System
  • Load Template Files
  • Create Forms
  • Process Form Data
  • Customize Form Field Validation
Module 21: Models
  • Define Database Models
  • Use Model Fields
  • Populate a Database, CURD
  • Use QuerySets
Module 22: Data Science for AI and Machine Learning Using Python
  • Foundation of Machine Learning
  • Supervised Machine Learning – Regression
  • Machine Learning – Classification
  • Test Analytics
  • Time Series
Module 23: Python for Data Analysis – NumPy
  • Introduction of NumPy
  • NumPy Array
  • NumPy Array Indexing
  • NumPy Operations
Module 24: Python for Data Analysis – Pandas
  • Introduction to Pandas
  • Series
  • DataFrames
  • Missing Data
  • Merging Joining and Concatenating
  • Operations
  • Data Input and Output
Module 25: Python for Data Visualization – Matplotlib
  • Introduction to Matplotlib
  • Matplotlib
  • Pandas Data Visualization
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Course Prerequisites
  • Some programming experience is useful, yet not required.