60 Minute Python Crash Course – Building a Solid Foundation!

The foundations of Python enabling them to then move into far more advanced programming

Understand how to create your own Python programs

Write a complete Python program that takes user input, processes and outputs the results

Write Python programs that can be used on Linux, Mac, Windows and Unix operating systems

The fundamental elements of programming which are transferrable into any language


  • Have a fun upbeat attitude and be ready to become awesome!
  • You need a laptop with internet access
  • No prior knowledge is required


In this course you will learn all of the FUNDAMENTAL programming techniques used within all programming languages to help you create AMAZING and EFFICIENT code!

  • Do you want to learn all the fundamental programming techniques quickly and effectively?
  • No more rummaging through YouTube videos, documentation and random stack-overflow posts to find the information you crave. This course gives you instant access to everything you need to know to get programming in Python, and puts it all right at your fingertips!
  • This comprehensive, in-depth and meticulously prepared course is going to teach you everything you need to know to program in Python! A – Z, it’s all here!

This course is great for those who haven’t programmed before, you guys will be given detailed video tutorials of each programming structure and we will continuously refer back to each structure within the course to solidify your knowledge.

What can you do with all this Python knowledge?

Python is HOT right now. The demand in the IT job market for Python skills keeps growing and growing. If you’re looking to get into programming as a career, level-up your existing career or open up new doors in the IT field, you really need to learn Python!

Perfect for Windows, Linux, Unix, Mac, the Web and More!

Once you’ve completed this course you’ll know how to write programs that will run on the Linux, Mac, and Windows operating systems. You can even take what you’ve learned and apply it web applications.

What will you achieve?

By the end of this course you will have built a solid foundation and have mastered many beginner techniques. Having learnt all of these new skills you can now move into the more advanced realms of programming by taking a look at the Complete Python Course 2019 where you will delve deeper into each programming structure. And with each video accurately planned and recorded I don’t waste your time, instead I teach you everything quick enough so you can easily understand it and go design!

Get a Certificate of Completion when you finish the course!


Who this course is for:

  • Those who want to open up doors in your IT career by learning one of the world’s most popular and in-demand programming language: Python.
  • For People New to Python
  • For Complete Programming Beginners
  • Students that want to learn all of the key aspects of programming

Course content

The Art of Doing: Video Game Basics with Python and Pygame

Fundamentals of the Pygame library and overall video game design.

How to create Pygame surfaces and draw on them.

How to blit (copy) images and render text.

How to add sound effects and music to your games.

How to handle user input via keyboard and mouse for game controls.

How to perform collision detection using pygame Rects.


  • Basic Python/computer science understanding.


Have you learned the fundamentals of Python and then asked yourself; what’s next?

If so, consider taking this course which will start you on your journey to making your own playable, fun, and rather addicting video games using Python and the Pygame library. 

So often, when students ask for advice they are told to, “Go build something” or “Get involved on a project” but have no idea what projects to build or get involved in.

This course will set you on your way! In this course I will walk you though, step by step, the fundamentals of video game design with Python and Pgyame.  We will cover all of the basics including:

  • Concepts of the main game loop, frames per second, and a clock.
  • Creating a surface and drawing to it.
  • Blitting (copying) images and rendering text to a surface.
  • Adding sound effects and music.
  • Handling keyboard and mouse input for player movement and control.
  • Basic collision detection methods

By the end of this course, I hope for two things:

  1. You will want to continue learning and consider about Pygame and Python and enroll in the full course!
  2. Have the confidence and knowledge to begin making your own basic arcade style games with Python!

Good luck and I hope to see you in our next video!

Who this course is for:

  • Beginner Python developers curious about video game design and the Pygame library.
  • Beginner Python developers who have a love for classic style arcade games.

Course content

Exception Handling in Python 3 – try, except, else, finally

Student can get much perfection on Python Fundamentals and Exception Handling


  • It’s desirable to have some minimum basic knowledge of English


As the part of Exception Handling, we will cover the following topics.

1. Syntax Error vs Runtime Error

2. The 3 Most Important Questions about Exception Handling

3. Default Exception Handling and Exception Hierarchy

4. Customized Exception Handling by using try-except

5. Control flow in try-except

6. How to print Exception Information to the console?

7. try with multiple except blocks?

8. Single except block that can handle multiple different exceptions

9. Default Except Block & Various except block syntaxes

10. finally block purpose and Speciality

11. finally block vs os._exit(0)

12. Important Interview Question: difference between finally block and destructor

13. Control Flow in try-except-finally

14. Nested try-except-finally theory and demo program

15. Control Flow in Nested try-except-finally

16. else block with try-except-finally theory

17. else block with try-except-finally demo programs

18. Various possible combinations of try-except-else-finally

19. Types of Exceptions-Predefined and User Defined

20. How to define and raise Customized Exceptions & Demo Program

Who this course is for:

  • Anyone looking to know basics of Python
  • Anyone looking to clear Python Interviews
  • Anyone looking to clear Python Certification
  • Anyone to get perfection on day to day coding requirements on Python Language Fundamentals and Exception Handling Concepts

Course content

Python Basics: Directories, Arrays, Tuples and Structures

A Brief Introduction to Python

Learning about Data Variables

Learning about Tuples, Pythons Language Strucutre

About Python Dictionary

Operators in Python

Introduction to Arrays and Lists on Python


  • No expereince required. The course is here to teach you the basics.


The course is a beginner’s course that seeks to introduce the coding language of Python to users and teaches them how to use the program. This introduction is broken up into six parts with the hope that the learner furthers their knowledge on their own or through additional courses once complete.

The course begins by teaching the learner how to download and use Python for the first time and how the program works. The second part of the courses describes and illustrates what variables are in Python and how to create them on your own. The third part of the course seeks to educate learners on tuples, the data structures of Python and how they serve to organise your data efficiently and effectively. This organisation of your data is later built upon through the fourth part of the course, as it attempts to train learners in dictionaries and the differences between tuples and dictionaries. This understanding allows learners to understand the differences and apply them in the real world. The fifth part of the course educates learners in operators and conditional statements. Operators are the tools utilised to operate mathematical tasks and operations in Python making it a useful tool to know. Finally, the course ends of with the differences between an array and a list through a step-by-step learning exercise. This exercise, much like the previous lessons, serves to teach students in a construct manner that builds from one lesson to the next.

Who this course is for:

  • Beginner Python Developers
  • Students Learning Python at School
  • People wanting to Learn How to Uterlise Python

Course content

Learn Python: Python in 80 Minutes for Beginners (2023)

Writing and running Python source code

Basic understanding of Python and how it works, as well as programming in general

Pre-requisite Python skills to move into specific branches

Basics of printing to the console

Understanding and working with different data types

How conditions and loops work

Getting user input

Creating and calling functions

Reading and writing to files

Creating and working with classes and objects


  • Working computer
  • Internet connection
  • No prior knowledge of Python
  • No previous programming experience


Welcome to the Python in 80 Minutes course for beginners. This course will go through the fundamentals of programming with Python. By the end of the course you will have gained enough knowledge to move on to different branches or continue to learn more advanced topics with Python. The course includes 6 quizzes and 4 coding exercises that will help you through your learning process. Keep in mind that this course will only teach the basics of Python, so if you are looking to learn more advanced topics, this is not the right course for you. This course is best for those who are looking to learn the basics of Python or just people looking to revise their basic Python knowledge. The course only takes 80 minutes, so if you have any doubts about learning programming, think about how much a new skill can help you in life, from automating your boring task to starting a career in programming.

This course will be covering the following topics:

  • Installing and setting up Python and PyCharm
  • The basics of Python
  • Using conditions (if else elif)
  • Using loops (while for)
  • Getting user input
  • Handling errors
  • Creating and working with files
  • Reading and writing to and from files
  • Working with classes and objects

Who this course is for:

  • Beginners who are looking to learn the basics of Python
  • People looking to revise their Python knowledge

Course content

R and Python coding with Prython

Learn how to use Prython for coding both R and Python projects

Design complex data science projects in Prython


  • Know some Python and/or R
  • Basic knowledge about data science and analytics


In this course we will learn how to use Prython, which offers a different way of coding than existing R/Python IDEs. It allows us to drop our code into panels that we place and connect in a canvas. In a normal IDE your code will run linearly from start to end, making it really hard to create sub-experiments/tests, and also to organise your project clearly. In Prython each panel accepts multiple IN and OUT connections, effectively transforming it into a 2D Jupiter notebook. It also has a wide array of tools that complement this canvas functionality: such as displaying dataframes next to the panels that modified them, allowing you to freeze your outputs, attaching consoles, navigation markers, etc.

We assume that the student is already familiar with R or Python, and some familiarity with matplotlib, scikit-learn,or keras would be beneficial as well.

Who this course is for:

  • Python and R practitioners with a focus on data science
  • ML engineers
  • Statisticians, engineers, and economists designing statistical models

Course content

Python with AI

Get started with Python programming

Understand Python fundamentals such as print, input, data conversion, if statement

Programming with confidence

Be ready to learn advanced Python programming


  • This course is for absolute beginners! No programming experience is required. If you can surf online, you are good to go.


Python programming is fun and useful, but starting from zero can be intimidating.

This course is designed to remove the intimidation factor of Python programming. It is for elementary or secondary students who are curious about Python programming, or who are scared of programming. The course provides bite-size videos. Each video covers one topic in about 10 minutes. The coding demos will show every steps. You can easily follow along and start to write Python programs.

There is no jargons, just plain explanations!

If you’re an adult and want to have a taste of Python programming, this is for you as well. Who would mind a quick and easy start?

The students will

  • Start with the general concept of Python, such as what it is and what it can do.
  • Learn how to install required software for Python programming.
  • Learn basic Python statements, such as print, input, data conversion, and if statements.
  • Practice Python coding.
  • Take pop quizzes to check knowledge understanding.
  • Write chatbot and math quiz programs.

After the course, the students will be able to:

  • Understand the general programming concept and process.
  • Understand what domains Python can be used.
  • Get comfortable with Visual Studio Code (Integrated Development Environment).
  • Understand Python fundamentals.
  • Ready for more advanced Python programming.

Who this course is for:

  • This course is for absolute beginners! It’s for everyone who wants to learn Python or who is scared of programming.

Course content

Data Science: Intro To Deep Learning With Python In 2021

Understand the intuition behind Artificial Neural Networks

Build artificial neural networks with Tensorflow

Classify images, data using deep learning

Apply Convolutional Neural Networks in practice


  • Some prior coding experience with python is required.


Neural networks are a family of machine learning algorithms that are generating a lot of excitement. They are a technique that is inspired by how the neurons in our brains function. They are based on a simple idea: given certain parameters, it is possible to combine them in order to predict a certain result. For example, if you know the number of pixels in an image, there are ways of knowing which number is written in the image. The data that enters passes through various “ layers” in which a series of adjusted learning rules are applied by a weighted function. After passing through the last layer, the results are compared with the “correct” results, and the parameters are adjusted.

Although the algorithms and the learning process in general are complex, one the network has learned, it can freeze the various weights and function in a memory or execution mode. Google uses these types of algorithms, for example, for image searches.

There is no single definition for the meaning of Deep Learning. In general, when we talk of Deep Learning, we are referring to a group of Machine Learning algorithms based on neural networks that, as we have seen, are characterized by cascade data processing. The entrance signal passes through the various stages, and in each one, they are subjected to a non-linear transformation. This helps to extract and transform the variable according to the determined parameters (weights or boundaries). There isn’t an established limit for the number of stages that a neural network must contain to be considered Deep Learning. However, it is thought that Deep Learning arose in the 80’s, using a model which had 5 or 6 layers. It was (and is) called the neocognitron and was created by the Japanese researcher Kunihiki Fukushima. Neural networks are very effective in identifying patterns.

An example worth highlighting of the application of Deep Learning is the project carried out by Google and the Universities of Stanford and Massachusetts. It aimed to improve the natural language processing techniques of a type of AI called Recurrent Neural Network Language Model (RNNLM). It’s used for automatic translations and creating subtitles, among other thing. Basically, it builds up phrases word by words, basing each word on the previous one and in this way, it can even write poems.

Module 1

1. Introduction to Deep Learning and TensorFlow

2. Basics of Neural Networks

3. Designing a shallow neural network (Scratch and python) (Project)

4. Deeper neural network using TensorFlow. (Project)

Who this course is for:

  • Beginners In Python
  • Beginners In Deep Learning
  • Beginners In Machine Learning

Course content

Introduction to Data Science using Python (Module 1/3)

Understand the basics of Data Science and Analytics

Understand how to use Python and Scikit learn

Get a good understanding of all buzz words like “Data Science”, “Machine learning”, “Data Scientist” etc.


  • This course does not have any pre-requisities. All you need is a Windows or a MAC machine.


Are you completely new to Data science?

Have you been hearing these buzz words like Machine learning, Data Science, Data Scientist, Text analytics, Statistics and don’t know what this is?

Do you want to start or switch career to Data Science and analytics?

If yes, then I have a new course for you. In this course, I cover the absolute basics of Data Science and Machine learning. This course will not cover in-depth algorithms. I have split this course into 3 Modules. This module, takes a 500,000ft. view of what Data science is and how is it used. We will go through commonly used terms and write some code in Python. I spend some time walking you through different career areas in the Business Intelligence Stack, where does Data Science fit in, What is Data Science and what are the tools you will need to get started. I will be using Python and Scikit-Learn Package in this course. I am not assuming any prior knowledge in this area. I have given some reading materials, which will help you solidify the concepts that are discussed in this lectures.

This course will the first data science course in a series of courses. Consider this course as a 101 level course, where I don’t go too much deep into any particular statistical area, but rather just cover enough to raise your curiosity in the field of Data Science and Analytics.

The other modules will cover more complex concepts. 

Who this course is for:

  • Anyone who wants to learn about Data Science from absolute scratch.
  • Anyone who wants to switch or make a career in Data Science and Analytics
  • Anyone who is curious to know what is Data Science and what does a Data Scientist do in his/her day job.

Course content

Hands-on Machine Learning for Stock Trading [Python]

How to create a Neural Network with Python

How to prepare data for Time Series Analysis

How to evaluate Machine Learning models

How to perform a reliable backtest with Python


  • Basic knowledge of Python


Enter the world of Neural Networks and Financial Forecasting with this free course.

Can you forecast the returns of your favorite stock using Machine Learning?

Artificial Intelligence is certainly changing the world:

From the way we get our content, autonomous driving, medical advances to art creation.

Financial Machine Learning is one of the industries with a bigger impact on these technologies, from Roboadvisors to Algorithmic Trading.

Most recommendations made by firms are based on Artificial Intelligence nowadays, rendering most conventional analysts useless.

The same happens for traders, not many years ago trading was done manually, currently a huge share of the market is being traded by AI.

These advances have changed the game, gaining insight with edges the human eye can’t see anymore.

While the biggest financial institutions have been trading using Artificial Intelligence for years, most retail traders don’t know how to use nor benefit from them, we are here to change that.

Roll up your sleeves with this hands-on project where you are going to learn by doing and interacting with code, completely from scratch.

In this course you are going to learn how to:

  • Download Historical Data from your code, automatically.
  • Prepare your data with the most suitable indicators.
  • How to label and prepare data to feed our model.
  • Prepare a Neural Network.
  • Evaluate models.
  • Backtest your ML Model.
  • Create accurate stock forecasts.

We hope you enjoy this course.

Genbox Trading

Who this course is for:

  • traders and coders who wants to use Machine Learning

Course content