Course Description

Python is developed under an OSI-approved open source license, making it freely usable and distributable, even for commercial use. Python is a general-purpose programming language. Created nearly 30 years ago, it is now one of the most popular languages out there to use. Its popularity is particularly important in the data science and machine learning fields. But it is also a language that is easy to learn, and that is why it has become the language most taught in universities.

Python interpreters are available for the main operating systems as well (Linux, Mac OS, Windows, Android, iOS, BSD, etc.) so it’s very flexible in where it is used. Python has a simple syntax that makes it suitable for learning to program as a first language. The learning curve is smoother than other languages such as Java, which quickly requires learning about Object Oriented Programming or C/C++ that require understanding pointers. Still, it’s possible to learn about OOP or functional programming in Python when the time comes.

Where is Python Used?

  • Web Development, using the frameworks Django, Flask, Pylons
  • Data Science and Visualization using Numpy, Pandas and Matplotlib
  • Machine learning with Tensorflow and Scikit-learn
  • Desktop applications with PyQt, Gtk, wxWidgets and many more
  • Mobile applications using Kivy or BeeWare
  • Education: Python is a great language to learn to program

How much can you make?

The average salary for a Python Developer is $117,155 per year in the United States. You can just search for Python jobs and see the ranges from $20/hr to over $40/hr.

This course will teach you and show you the basics of Python programming. We will go over concepts like loops, variables, operators, syntax and coding practices. With each module, we will build upon your knowledge from the previous module. This reinforces all the concepts along the way and at the end of some modules you will work on exercises to prove to yourself you can do this.

After taking this course you will be ready to move on to a move advanced course allowing you to build on the foundation this course provides. You will be making more sophisticated and more robust programs in no time using your new skills.

For complete information on this certification course, please visit the Python website for details.

Introduction to Python

Additional information

8 Hours 49 Minutes

25 Course Videos

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Course Videos

This course contains the following modules and videos. Click the down arror to view video details.

Module 1: Getting Started with Python
  • Intro to Course and Instructor
  • Getting Started with Python
Module 2: Working with Primitive Data Types
  • Working with Primitive Data Types
  • Working with Primitive Data Types Part 2
  • Working with Primitive Data Types Part 3
  • Working with Primitive Data Types Part4
  • Working with Primitive Data Types Part4 Answers
Module 3: Working with Multiple Assignments Statements
  • Working with Multiple Assignments Statements
Module 4: Convert Types in Python
  • Convert Types in Python
Module 5: Creating Lists
  • Creating Lists
Module 6: Modifying Lists
  • Modifying Lists
Module 7: Sorting and Reversing Lists
  • Sorting and Reversing Lists
Module 8: Slicing Lists
  • Slicing Lists
Module 9: Working With Operators
  • Working With Operators
  • Working With Operators Part2
  • Working With Operators Part3
Module 10: Determining Operator Precedence
  • Determining Operator Precedence
Module 11: Working with IF Statements
  • Working with IF Statements
Module 12: Working With For Loops
  • Working With For Loops
Module 13: Working With While Loops
  • Working With While Loops
Module 14: Nesting for Loops
  • Nesting for Loops
Module 15: Reading Files
  • Reading Files Part1
  • Reading Files Part2
Module 16: More on Files
  • More on Files
Module 17: Merging Emails
  • Merging Emails
Module 18: Reading Console Inputs and Formatting Outputs
  • Reading Console Inputs and Formatting Outputs
Module 19: Reading Command Line Argument
  • Reading Command Line Argument
Module 20: Defining Functions
  • Defining Functions
Module 21: Using Default Argument
  • Using Default Argument
Module 22: Using Keyword and Positional Arguments
  • Using Keyword and Positional Arguments
Module 23: Handling Exceptions
  • Handling Exceptions
Module 24: Using Math and Random Modules
  • Using Math and Random Modules
Module 25: Displaying Daytime Working Directory and File Metadata
  • Displaying Daytime Working Directory and File Metadata

Introduction to Python

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Introduction to Python

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Introduction to Python

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Introduction to Python

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Introduction to Python

Practice Quizzes and Exams

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Introduction to Python

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