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Programming – PYTHON Programming

Learn Python Programming Masterclass

Best Sellers

4.5 (352 ratings)

  • 254 students enrolled
  • by Experts
  • 27 to 5 Nov, 21

What you'll gain

  • Have a fundamental understanding of the Python programming language.
  • Have the skills and understanding of Python to confidently apply for Python programming jobs.
  • Acquire the pre-requisite Python skills to move into specific branches - Machine Learning, Data Science, etc..
  • Add the Python Object-Oriented Programming (OOP) skills to your résumé.
  • Understand how to create your own Python programs.
  • Learn Python from experienced professional software developers.
  • Understand both Python 2 and Python 3.

Whether you want to:

  • Build the skills you need to get your first Python programming job
  • Move to a more senior software developer position
  • Get started with Machine Learning, Data Science or other hot areas that Python specializes in
  • Or just learn Python to be able to create your own Python apps quickly.

Then you need a solid foundation in Python programming. And this course is designed to give you those core skills, fast.

This course is aimed at complete beginners who have never programmed before, as well as existing programmers who want to increase their career options by learning Python.

The fact is, Python is one of the most popular programming languages in the world – Huge companies like Google use it in mission critical applications like Google Search.

And Python is the number one language choice for machine learning, data science and artificial intelligence. To get those high paying jobs you need an expert knowledge of Python, and that’s what you will get from this course.

By the end of the course you’ll be able to apply in confidence for Python programming jobs. And yes, this applies even if you have never programmed before. With the right skills which you will learn in this course, you can become employable and valuable in the eyes of future employers.

And there are many more students who love the course – check out all the reviews for yourself.

Will this course give you core python skills?

Yes it will.  There are a range of exciting opportunities for Python developers. All of them require a solid understanding of Python, and that’s what you will learn in this course.

Will the course teach me data science, machine learning and artificial intelligence?

No, it won’t do that – All of these topics are branches of Python programming and will give machine learning and deep learning based examples too.  And all of them require a solid understanding of the Python language.

Nearly all courses on these topics assume that you understand Python, and without it you will quickly become lost and confused.

This course will give you that core, solid understanding of the Python programming language.

By the end of the course you will be ready to apply for Python programming positions as well as move on to specific areas of Python, as listed above.

Here’s just some of what you’ll learn

(It’s okay if you don’t understand all this yet, you will in the course)

All the essential Python keywords, operators, statements, and expressions needed to fully understand exactly what you’re coding and why - making programming easy to grasp and less frustrating

You will learn the answers to questions like What is the Python For Loop, what is Python used for, how Python switch the traditional syntax of code, and more.

Complete chapters on object-oriented programming and many other aspects of Python

Although this is primarily a Python 3 course, a python developer will need to work with Python 2 projects from time to time – We’ll show the difference in both versions to make sure you understand how things work differently in each version.

Does the course get updated?

It’s no secret how technology is advancing at a rapid rate. New, more powerful hardware and software are being released every day, meaning it’s crucial to stay on top with the latest knowledge.

A lot of other courses on galwin get released once, and never get updated.  Learning from an outdated course and/or an outdated version of Python can be counter  productive and even worse it could teach you the wrong way to do things.

For example if you apply some parts of Python 2 to Python 3 code, you will get completely different results.

We cover differences like this in the course and also continually update the course as well.

What if you have questions?

As if this course wasn’t complete enough, we offer full support, answering any questions you have 7 days a week (whereas many instructors answer just once per week, or not at all).

Ready to get started, developer?

Enrol now using the “Register” button on the right, and get started on your way to creative, advanced Python brilliance. Or, take this course for a free spin using the preview feature, so you know you’re 100% certain this course is for you.

See you on the inside (hurry, your Python class is waiting!)

Who this course is for:

  • Beginners with no previous programming experience looking to obtain the skills to get their first programming job.
  • Anyone looking to build the minimum Python programming skills necessary as a pre-requisites for moving into machine learning, data science, and artificial intelligence.
  • Existing programmers who want to improve their career options by learning the Python programming language.

If you are an expert Python programmer with extensive knowledge, and many years’ experience, then this course is probably not for you.


  • Our First Python Program
  • Printing in Python
  • Printing text
  • Printing the result of a calculation
  • Strings in Python
  • The Escape Character
  • Printing tabs
  • More on Escape Characters in Strings
  • Variables and Types
  • Python is a Strongly Typed Language
  • Using a Debugger in IntelliJ or Pycharm (front)
  • PEP8: The Python Style Guide(front)
  • Numeric Data Types in Python
  • Numeric Operators
  • Expressions
  • Integer division
  • Operator Precedence

Python Input and Output (I/O)

  • Introduction to the Section
  • Reading and writing text files
  • Writing Text Files
  • Appending to Files and Challenge
  • Writing Binary Files Manually

Flow Control statements in Python

  • Introduction to Blocks and Statements
  • if Statements
  • elif
  • More on if, elif and else
  • if, elif, and else in the Debugger
  • Adding a Second Guess
  • Conditional Operators
  • Challenge Solution
  • Using and, or, in Conditions
  • Simplify Chained Comparison
  • Boolean Expression True and False
  • Truthy Values
  • in and not in
  • if Challenge
  • Solution to if Challenge
  • for loops
  • Stepping through a for loop
  • for loops Extracting Values from User Input
  • Iterating Over a Range
  • More About Ranges
  • For loop with step
  • Nested for loops
  • continue
  • break
  • Initializing Variables and None
  • while  and do loops
  • More on while loops and do loops
  • Break in a while loop
  • The Random Module and Import
  • Binary Search
  • Hi Lo Game

Pass Statement and Complete the Hi Lo Game

  • Testing the Hi Lo Game
  • Augmented Assignment
  • Refactoring Code
  • else in a loop
  • else in the Hi Lo Game
  • Conditional Debugging
  • Another else Example
  • Changing the Condition

String in python

  • The str String Data Type
  • Negative Indexing in Strings
  • Slicing
  • Slicing with Negative Numbers
  • Using a Step in a Slice
  • Slicing Backwards
  • Challenge Solution and Slicing Idioms
  • String Operators
  • String Replacement Fields
  • String Formatting
  • f-strings
  • Python 2 String Interpolation
  • Section Summary
  • The Basics of Python

List and Tuples

  • Introduction to Sequence Types
  • Lists
  • Immutable Objects
  • Mutable Objects
  • Binding Multiple Names to a List
  • Common Sequence Operations
  • Operations on Mutable Sequences
  • Appending to a List
  • Mini Challenge Solution
  • Iterating Over a List
  • The enumerate Function
  • Improving our Code
  • Removing Items from a List
  • Sorting Lists
  • Built-in Functions
  • Sorting Things
  • Case-Insensitive Sorting
  • Creating Lists
  • Replacing a slice
  • Deleting Items from a List
  • Safely removing values from a list
  • Removing the High Values
  • Test, Test and Test. Then Test Again!
  • Testing the Program
  • Removing Items from a List Backwards
  • The Reversed Function
  • Algorithms Performance
  • Summary so far
  • Nested Lists & Code Style
  • Processing Nested Lists
  • Solution to nospam Challenge
  • Function Signatures
  • print revisited
  • The join Method
  • The split Method
  • Solution to Mini Challenge
  • Tuples introduction
  • Tuples are Immutable
  • Unpacking a Tuple
  • Practical uses for Unpacking Tuples
  • More Unpacking
  • Nested Tuples and Lists
  • Solution to Unpacking Challenge
  • Constants in Python

Dictionaries and set

  • Introduction
  • What is a dictionary?
  • Iterating over a dictionary
  • Adding items to a dictionary
  • Changing values in a dictionary
  • Removing items from a dictionary
  • Using `in` with a dictionary
  • Dictionary menu challenge solution
  • Using a list with a dictionary
  • Adding items to a dictionary
  • Using several dictionaries together
  • Checking quantities - the code
  • Solution: Create a shopping list challenge
  • Wrong decisions don't have to be fatal
  • The setdefault method
  • APIs and a mobile phone demo
  • The `dict` documentation
  • The remaining `dict` methods
  • The dict `update` method
  • The dict `values` method
  • References to mutable objects
  • Hash functions
  • A really bad hashing function
  • Hash tables
  • Completing our simple dictionary implementation
  • Hash functions and security
  • hashlib, the secure hash module
  • Python sets
  • Implications of sets being unordered
  • set membership
  • Testing set membership is fast
  • Adding items to a set
  • Using a set to remove duplicate values
  • Deleting items from a set
  • The `discard` method
  • The `remove` method
  • The `pop` method
  • set union
  • Set union in practice
  • Union update
  • Advantage of the set operation methods over the operators
  • Set intersection
  • Set intersection in practice
  • Set difference
  • Set difference in practice
  • Set symmetric difference
  • subsets and supersets
  • subsets and supersets in Python

Function in Python

  • Introduction
  • Defining a function
  • Program flow when calling a function
  • Parameters and arguments
  • Debugging with parameters
  • Palindromes
  • Palindrome challenge solution
  • Sentence challenge solution
  • Functions calling functions
  • Returning values
  • get_integer Challenge solution
  • Returning None
  • Functions that perform actions
  • Handling invalid arguments
  • width challenge solution
  • Default parameter values
  • Keyword arguments
  • Docstrings
  • Writing a Docstring
  • How professional is that!
  • Solution to Docstrings challenge
  • Fibonacci Numbers
  • Writing a fibonacci function
  • Function annotations and type hints
  • Function annotations with default values
  • Solution to banner_text Docstring challenge
  • A function to test our HiLo game
  • Counting correct guesses
  • Playing Fizz Buzz
  • Playing Fizz Buzz Solution
  • Factorial function
  • *args
  • colour_print with multiple arguments
  • Rules for variable number of arguments
  • Defining different parameter types
  • Variable number of arguments

Global and local variables

  • Global Variables
  • Global Keyword
  • Scope in Functions
  • Importing Techniques
  • Underscores in Python code
  • Namespaces, more on Scope and Recursion
  • Recursion with OS Module and Filesystem and Nonlocal keyword
  • Nonlocal keyword, Free and LEGB

Modules in Python

  • Introduction to the Section
  • Modules and import
  • The standard Python library
  • Web Browser Module
  • Time and DateTime in Python
  • Python date time module
  • Python datetime.strftime()
  • Python datetime.strptime()
  • Get Current time
  • Timestamp to datetime
  • Python time module
  • Python tim.sleep()

Oops Concept in Python

  • Python oop
  • Python class
  • Python inheritance
  • Multiple inheritance

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This course includes
  • 6:00 pm to 8:00 pm
  • E materials
  • 4 Workouts
  • Online
  • Google Meet
  • E - Certificate of Completion