AI BootCamp (Module 1 Crash Course)

Launch
Natural Language Processing
Recommendation Systems
Decisions and Ethics
Machine Learning Algorithms
(Optional) Python and Orange
Launch

1. Understand what machine learning is
2. Be able to build a simple machine learning model

CHALLENGE

• Be able to make changes to a simple machine learning model

Natural Language Processing

1. Understand what a chatbot is
2. Be able to build a natural language recognition model

CHALLENGE

• Recognise the advantages of natural language processing
• Appreciate real life applications of chatbots

Recommendation Systems

1. Understand how machine learning can be used to make recommendations
2. Be able to build a simple recommendations system

CHALLENGE

• Be able to adapt a recommendation system to include new criteria
• Understand what a Filter Bubble is

Decisions and Ethics

1. Understand how Machine Learning is used to make decisions
2. Understand potential issues with the application of machine learning

CHALLENGE

• Be able to evaluate the impact of ethical considerations in the application of Machine Learning

Machine Learning Algorithms

1. Understand the difference between supervised and unsupervised learning
2. Understand basic machine learning algorithms

CHALLENGE

• Be able to use basic machine learning algorithms
• Understand what a neural network is

(Optional) Python and Orange

1. Be able to use machine learning tools to visualise data

CHALLENGE

• Be able to use python to import data and run basic machine learning algorithms

LEARNING OUTCOMES

• Machine learning model that can sort images
• Machine learning model that can recognise natural language commands
• Machine learning model that can recommend the reading age of a book based on data about the book
• Presentation or report summarising key points
• Completed algorithm exercises
• Data visualiastions using Orange
• Python code for importing data and running machine learning algorithms (decision trees and kNN)