My lessons are ideally for complete beginners to programming within the age range of 8-16. Programming can be a very creative and fun skill to learn. I focus on providing a solid understanding of the core programming concepts so that we can apply what we learn creatively to make interesting programs. I have my own content that covers fundamental computing concepts in an accessible way and I'm am working on more. I would be happy to provide general tutoring for Python or Javascript to help with revision or exams. I think the best and easiest way to learn a skill is to ensure that you enjoy doing it. This way of thinking guides how I tutor. Together, lets learn to code.

Python is an open source language, used today mostly in back-end technology. It's easy to learn, and setting it up on a PC takes no time at all. There are modules just a Google away, if you have a particular interest - such as in data, or AI. In this class, you'll learn about basic syntax, documenting, and the Software Development Life Cycle - and how it may be used in a workplace - while moving onto more complex things such as procedures, and a GUI (Graphical User Interface).

Teaching python to beginners! In these classes, you will learn the basics of python programming, functions, lists, sets, and much more with practice assignments and assessments... I have experience in teaching python to university peers.

My lessons are designed to take you from simply following code to genuinely understanding how data science works. We can cover the complete data science process, including data cleaning, exploratory data analysis, feature engineering, visualisation, statistics, machine learning, model evaluation and communicating results. Depending on your goals, lessons can include: Python, pandas, NumPy and scikit-learn Data cleaning and exploratory analysis Regression and classification Decision trees, random forests and boosting Clustering and dimensionality reduction Cross-validation and model evaluation Feature engineering and model interpretation Neural networks and deep learning foundations Bayesian modelling and PyMC Portfolio and interview preparation Support understanding university modules and projects I use diagrams, analogies and practical demonstrations to make difficult ideas easier to understand. We will normally begin with an intuitive explanation, look at the underlying logic or mathematics, and then implement the concept in Python. Lessons are personalised around your level. Complete beginners receive a structured learning path, while experienced students can focus on advanced topics, project guidance, debugging or interview preparation. You will be encouraged to explain ideas back to me, interpret results and make your own modelling decisions. My goal is not only to help you produce working code, but to help you become an independent and confident data scientist.