A Practical Introduction to Artificial Intelligence

Course Aim/Overview

• What is AI?: Understand the huge breadth of possible AI techniques.  Understand a little of this history.  Understand what an algorithm is.
• Reinforcement Learning: Understand this useful AI technique for training “agents” to perform a task.
• Teach an Agent to Solve a Maze: Teach an agent to find its way out of a maze.
• Teach an Agent to Play a Game: Teach an agent to play a simple 2-player game like noughts and crosses.
• Teach a robot to Walk: Teach a simple robot simulation to walk.

The course will involve coding with the Python programming language, which is a popular programming language used by professional coders. The course is aimed at beginners, so template code will be provided and lots of non-coding activities will be provided.

This course is available at our London campus or online.

Why this course?

Our awareness of artificial intelligence (AI) is increasing, and AI is having a real impact on our lives. Our previously “dumb” machines are becoming “smart” and the organisations we deal with daily are increasingly using “algorithms” to make decisions about us.

Understanding how AI works will help you interact with the technology-driven world in a more informed way.

This course has been developed to provide a gentle introduction to artificial intelligence for those starting to explore this fascinating field.

Who is the course for?

• Individuals wanting to start out on a career in AI or Computer Science, e.g. pre-university students, career changers
• Individuals working with AI specialists who want to better understand what they do to improve their interactions with them. e.g. project managers, software developers
• Individuals curious about how AI and algorithms work

Course materials

• Students should bring a laptop (Windows, Mac, or Linux).
• Students may be required to install software, so administrative privileges on the computer may be required.  Alternatively, students should have a Google account to use the online platform.  Instructions will be sent before the course.
• Course notes and code will be provided.

Prerequisites

• You should be comfortable using your computer to install programs, download files, organise files etc.
• No specific programming experience is needed, but any exposure to programming or scripting would be useful

Essential reading

Whilst not essential, students may want to read some of these very accessible books on AI to get a feel for the background of the subject:

• Hello World Hannah Fry
• AI: Its nature and future Margaret A. Boden

Learning objectives

On completion of this course, students will be able to:

• Analyse and design computable representations of problems
• Explain the mechanisms of reinforcement learning
• Create trainable agents to solve certain problems
• Write Python code to implement reinforcement-learning agents