This class runs like an after school club. There is a class once a week every week at the same time. Minecraft coding sessions last an hour.

Python Coding 1, 2 & 3, Summer Term Timetable 2026:

Duration: 8/9  weeks
Frequency: Once a week
Course Fee: £144 – £162

Note (no sessions): 4th May 2026 (Bank holiday) & 25th May to 29th May 2026 (Half term break)

Challenges may vary depending on the child’s age/ability as we have multiple streams running within each session.

Age Requirement: 10+

What you would need: 

– A computer or tablet with the Zoom web conferencing software installed.

– A laptop/computer (PC or Mac) with Python installed (download here)

Experience:  
No prior coding experience necessary for beginner Python. If you have been to one of our camps before or attended a term-long beginner & intermediate Python classes, then we would suggest booking the Intermediate & advanced Python classes respectively which covers more advanced topics.

Beginner Python Coding

Students will learn to code in Python and create fun games and useful applications. Python is particularly suitable for this age group because it is concise, easy to read and has multiple applications in the real world (web development, app development and other scientific uses such as data science). It is the most popular programming language in the world and is widely used by all the leading tech companies such as Google, Amazon and Facebook.

Intermediate Python Coding

Intermediate Python Coding is suitable for students who have either completed our Python Coding 1 course or who have experience coding in Python. It is designed for late primary to secondary aged students who are looking to take their Python programming skills to the next level.

Advanced Python Coding

Advanced Python Coding is designed for confident coders aged 11 or over, looking to apply their programming knowledge to data science and machine learning. Students will be introduced to Interactive Python Notebooks, a tool used by professionals to write and present their code.

We will then look at the “Pandas” library, a useful tool that allows us easily to describe and manipulate large amounts of data. We will then learn how to visualise our data by plotting graphs and spotting trends in the dataset. We’ll cover more useful libraries to add to our Data Science arsenal.

Finally, we will get a brief introduction to machine learning, the process of letting a computer recognise patterns and make predictions. In our case, this means recognising images that we give to it!