AI CORE Summer School

AI Core is launching an online summer school. This will be an ‘Introduction to Artificial Intelligence’. Specifically, the course is aimed at, but not limited to, pupils in Year 11, & Year 12, who are going into Year 13. That is to say, it is designed to offer an opportunity for the students to differentiate themselves when applying to university.

The summer school has been developed by the founding team of the AI Core, ex-Imperial students who founded the Machine Learning Society at Imperial College London. It will be led by Outstanding Student Achievement winner Haron Shams.

In essence, we will be teaching the real nuts and bolts that are being used in industry but in an accessible manner, being built on the school curriculum. With this purpose in mind, the AI Core Summer School is a definitive bridge between school and university.

Artificial Intelligence Summer School

An 8 session course designed to teach secondary school students how to code machine learning algorithms.

3 hours per week for 8 sessions fully remote, live & interactive training from AI Core: leading educator in artificial intelligence.

A Great opportunity

Get an edge on your personal statements by learning something useful this summer. Learn programming and machine learning that is practical and can solve real problems. This course offers a compelling opportunity for students to differentiate themselves in their personal statements.

Additionally, the skills learnt from this course will be complementary to those learnt at university and students can refer to and leverage their knowledge learnt on this course. The course teached the core skills that will power our future economy.

8 Sessions

Two

2 Hour Session
/ Per Week

The day and time of the session launch is the 23rd of July

£450

per student

A percentage of tuition from this course will be used to subsidise students from various backgrounds to join us.

Topics we will cover, week by week:

Break it down for me.

Week 1

Programming in Python

Data types, Functions, Classes

Introduction to programming one of the most powerful languages: Python

Week 2

Working with Data

Discover how a computer sees the world

Experience working with all kinds of data types

How to collect data and load it into your program

Week 3

Data Visualisation Libraries

Implement the most widely used data visualisation techniques

Pandas & Matplotlib (Python Libraries)

Week 4

The machine learning problem

What is the goal of machine learning?

How do we know if an ML algorithm is performing well?

Week 5

Regression and Optimisation

Build your first machine learning algorithm

Predict insurance prices from data

Working with multi-variate data

Week 6

P​ractical Tips for Machine Learning

Predict boris bike usage based on weather patterns

Debugging optimisation of learning algorithms

How do we increase the accuracy of our model? 

Week 7

Gradient Based optimisation

Using the chain rule to differentiate

Visualising a learning algorithm during training

Understanding the problem of local minima 

Week 8

Classification Algorithms

Predict the species of flowers

Why do we use the sigmoid function? 

Prerequisite knowledge

No prerequisite knowledge is necessary, this course has been developed to cater for the school curriculum and so is an accessible introduction to artificial intelligence. Experience in Python or other programming languages will be useful. In terms of maths, the only requirement is to know what differentiation is. One of the unique points of this course is that you get to look inside the “black box” and learn how to build it from scratch.

Though generally aimed at years 11, 12 and 13, there isn’t any age restriction. It is free for anyone to join as long as they meet the prerequisites listed above. 

Come attend some of our community driven events for a gateway into the world of AI.

Results. Everytime.

Students having finished this course will be adept in the basics of artificial intelligence and capable of taking the theory learnt in the summer school and putting it into practice; working with data, to visualise it and use machine learning to analyse, interpret and make predictions. A certificate will be received upon course completion.

A practical approach is taken with students getting their hands dirty coding from the first session. They will not only learn the maths and theory behind the algorithms, but code them from scratch using the numerical computation library, Numpy.

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