Siriwat N.
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Online Course
bestseller
free
Python Programmer Bootcamp
with
Giles McMullen-Klein
Master Python and solve real-world problems with computational thinking
83935 students already have enrolled
Skill level:
Basic
Duration:
20 hours
-
Lessons (11 hours)
-
Practice exams (1.08 hours)
-
Projects (23 hours)
- Lessons (11 hours)
- Practice exams (1.08 hours)
- Projects (23 hours)
CPE credits:
16
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
Accredited:
certificate
What You Learn
- Take the Python Programmer Bootcamp to improve your coding proficiency.
- Engage in practical challenges that boost your Python problem-solving skills.
- Work with IDEs like Spyder and Jupyter.
- Learn to create data visualizations using Python’s Matplotlib.
- Master object-oriented programming and complete a capstone project.
Topics & tools
theorypythonprogrammingdata visualization
Your instructor
Python Educator | Content Creator at Python Programmer (YouTube) | AI & Data Science
Track record
Bringing real-world expertise from leading global companies
Academic background
Bachelor's degree, Physics
Media and recognition
- Creator of Python Programmer YouTube channel, teaching worldwide
- Reviews books, courses & resources for aspiring Python developers
- Presents data science projects and practical coding tutorials
Course OVERVIEW
Description
CPE Credits: 16
Field of Study: Information Technology
Delivery Method: QAS Self Study
Delivery Method: QAS Self Study
This Python course will not only take your programming skills to the next level, but also give you a problem-solving superpower! In it, you will develop a thorough understanding of Python and its programming capabilities, as well as hone your computational thinking. Moreover, you will learn how to implement object-oriented programming (OOP), create Python charts in Matplotlib, and work with different IDEs like Spyder and Jupyter. As you progress , you’ll get to practice your skills with fun and challenging exercises like solving the Sierpinski Triangle and the Towers of Hanoi. Your instructor, Giles McMullen-Klein, is an Oxford-educated programmer who made proficient use of Python during his time at the University. Not only that but he is motivating, enthusiastic, and truly passionate about the programming language he teaches!
Prerequisites
- Python (any recent version, such as Python 3.8 or later) and Spyder IDE (included in the free Anaconda distribution)
Advanced preparation
- None
Curriculum
128 lessons
79 exercises
2 projects
5 exams
- 2. Setting up the environment10 MinSetting up Python can be one of the most challenging aspects of using it. There are so many different ways of installing it onto your computer and sometimes they can create conflicts that can be difficult to resolve. That’s why we’ve chosen to use Anaconda. It’s a simple installation, which we’ll walk through with you. You’ll have python up and running in a few minutes. Spyder is an IDE (integrated development environment) which is included with the Anaconda Python installation. IDEs are very useful when coding, as they put everything you need right at your fingertips. Here we show you the basics of Spyder.
- 3. Python basics + Hands-on Coding11 MinIt’s essential that you understand how the PRINT function works in Python. It’s what enables you to print output to the screen, it’s also useful when it comes to debugging - more on that later! Here you will receive a thorough grounding in how to use it.
- 4. Variables and strings - Exercises24 MinVariables are the building blocks of all programming languages. This section introduces them, explains what they are and why they’re so important. We will show you how they are used in python.
- 5. Conditionals44 MinIf you want a computer to make decisions then you need to use conditionals. Conditionals enable computers to choose different outcomes based on the value of a variable. They are very powerful and key to being able to code in Python.
- 6. For Loops63 MinComputers are very good at doing repetitive tasks. The for loop is one way of controlling how this is done. It allows you to request the computer to repeat blocks of code. In this section, you will learn how to use the for loop and just how handy it can be. We then look at the other type of loop - the while loop. In this section, we also take a look at a python data type called a list. We explore how, why and when to use it.Intro to For loops FreeExercise FreeCoding exercise FreeA little more on variables FreeExercise FreeLists FreeExercise FreeCoding exercise FreeThe power of lists and loops and working together FreeCoding exercise FreeSome list methods FreeCoding exercise FreeWhile loops FreeCoding exercise FreeModulus FreeExercise FreeCoding exercise FreePractical challenge Free
- 7. Dictionaries48 MinAnother Python data type. It’s essential to understand what a dictionary is and how to use it. They are widely used in data applications. We explore their uses and some applications in this section. We also cover modules, which give python a whole new set of features. You will learn how to import and use modules and we will introduce you to the counters module: very powerful but often overlooked. You will be introduced to the tuple, another data type and we will cover the zip function too.Modules FreeDictionaries FreeExercise FreeCoding exercise FreeZip function FreeExercise FreeCoding exercise FreeMore string methods FreeCoding exercise FreeTuples FreeMore than 1 dimension FreeCoding exercise FreeImport counters (Part I) FreeCoding exercise FreeImport counters (Part II) FreePractice exam Free
- 8. Files and Functions32 MinPython can handle files. It can open files, read files, write to files and manipulate the content of files. In this section, we will introduce you to some of the more common file handling methods in python. We also take a closer look at functions. We also cover a very important topic in computer science: recursion.
- 9. Classes27 MinClasses and objects: what’s the difference and why does it matter? You will find out in this section. Everything in Python is an object, we will show you what this means and how it can help you to write better code. You will learn how to create your own objects, the difference between a method and a function and we will introduce the concept of inheritance.
- 10. General Tips7 MinWe have covered a lot of ground, in this section, we take a look at the bigger picture. You will receive general advice on how to become a better Python programmer.
- 11. Big O16 MinHow long will your algorithm take to run? How does it scale as the amount of data you process increases? These questions can be answered by considering Big O. We will explain what it is and how it is applied to algorithms in this section.
- 12. Advanced Python: Caesar two sum38 MinIn this section, we consider two well-known computer science problems and work through their solution with Python.Intro FreeCaesar cipher FreeJupyter notebook intro FreeCaesar cipher solution FreeCoding exercise FreeTwo sum FreeTwo sum solution FreeCoding exercise FreeCard class FreePlaying card class FreePlaying card class solution FreeCoding exercise FreeEncryption and Decryption in Python Project Free
- 13. Advanced Python: Matplotlib30 MinPython is so versatile, there are very few things you can’t do with it. One of its many strengths is data visualization. Matplotlib is a well-known data visualization module in python. We introduce you to it in this section and work through some interesting examples.
- 14. Advanced Python: Stacks40 MinData can be stored in various different ways, known as data structures. In this section, we will show you a very important data structure known as a stack. We explore what it is, how it’s used and how it can help us to solve problems, such as the famous computer science problem called ‘The Towers of Hanoi’.Intro to stacks FreeCoding a stack in Python FreePractical challenge - stacks FreeExercise FreeHint on solving the challenge FreeSolving the stacks challenge FreeCoding exercise FreeTowers of Hanoi FreeSome hints FreeCode for Tower of Hanoi FreeCoding exercise FreeEnumerate sets & none FreeCoding exercise Free
- 15. Search and sort27 MinTwo of the most important tasks for computers are searching and sorting. So much work has been done on how to optimize these tasks. In this section, we introduce you to the challenges they pose. We cover some famous searching and sorting algorithms.
- 16. Advanced Python: Cards and Coins14 MinIn this section, we put our python skills to use to solve some problems. We will make a credit card number validator using Luhn’s algorithm and we will write some python code to solve a famous maths puzzle.
- 17. Advanced Python: Debugging20 MinWhen you write code, it will contain mistakes! It’s unavoidable. Debugging is the process of going through your code, finding the mistakes and correcting them. We will teach you that process in this section. You will also be introduced to python’s module for using regular expressions: Regex.
- 18. Advanced Python: Strings and Expressions24 MinIn this section we dig deeper into strings. It is not mandatory to go through them, but such advanced topics are always the most interesting. We explore how to format numbers in specific ways and get familiar with regular expressions.
- 19. Capstone project - Computer Vision29 MinWorking through problems in Python could also be quite a challenging task. However, Python allows us to work on very complicated computational problems even with a limited programming knowledge. In this capstone project we simulate a real-world situation where we are asked to solve an extremely challenging problem, in order to build our research skills.
- 20. Further Exercises1 MinHere you will find some additional exercises that will help you reinforce what you have learned in the lessons. Hope you enjoy them!
- 21. Installing Python and Using Virtual Environments on Windows and Unix69 MinIn this section, we will learn how to install Python using virtual environments. That will enable you to set different sorts of sandbox versions of Python on your machine to avoid potential conflicts between different Python versions.Introduction FreeDownloading Python FreeSetting up the virtual environment FreeSharing a project - requirements file FreeDownloading and Installing Virtual Box & Setting up a Virtual Machine FreeInstalling Ubuntu on the Virtual Machine FreeSetting up a virtual environment on Ubuntu FreeIntroduction to the command line FreeHandling files on in the command line FreeCopying, moving and deleting files on the command line FreeEcho, environment variables and path FreeSection summary Free
- 22. PyCharm29 MinThis section introduces another highly functional IDE - PyCharm. Using PyCharm not only helps your Python programming, but familiarity with it is a common prerequisite for a career in data science.
- 23. Exception handling in Python25 MinException handling is one of the Python features that allow you to anticipate errors in your code and deal with them in advance. Although learning how to handle exceptions may seem challenging at first, it will prove to be an indispensable tool in your Python programming arsenal.
- 24. Farewell7 MinSome parting words of encouragement and a sincere thank you!
- 25. Course project and exam1030 Min
Free preview
1.1 What does the course cover
3 min
1.2 Why code? Why Python?
10 min
2.1 Installing Python
3 min
2.2 Introducing Spyder
7 min
3.1 PRINT function
11 min
4.1 The solution
2 min
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