Welcome to An Introduction to Technology-Assisted Decision-Making

Are you ready to revolutionise the way you make decisions? Say ‘Hello’ to technology-assisted decision-making! This course is designed to introduce you to the latest techniques and tools for making data-driven decisions with the help of technology. From linear programming to other optimisation algorithms, you’ll learn how to use mathematical models to find the best possible solutions to complex problems.

Gone are the days of making decisions based on gut instinct or incomplete information. With technology-assisted decision-making, you’ll be able to analyse vast amounts of data, identify patterns and trends, and use mathematical models to make informed decisions that drive success. Whether you’re working in finance, logistics, engineering, or any other field, technology-assisted decision-making can help you make better decisions, faster.

In this course, you’ll get hands-on experience with a variety of technology-assisted decision-making techniques. You’ll learn how to formulate optimisation problems, design mathematical models, and (optionally, for those who’d like to delve deeper) use specialised software to solve them. You’ll also learn how to evaluate the quality of your solutions, and how to communicate your results effectively to others.

This course is part of the Click Start collection of short courses provided by the University of Leeds. Click Start is a nationwide training programme developed by the Institute of Coding (IoC), supported by a consortium of industry leaders, educators, and outreach providers, and funded by Nominet. Click Start aims to diversify the tech industry and address the UK’s digital skills gap.

Learning outcomes

By the end of this course you will be able to:

• Explain what technology-assisted decision-making is, and what it is used for.
• Model a specific decision-making problem as a graph theory problem.
• Apply a simple procedure to solve a decision-making problem, using Kruskal’s algorithm.
• Assess the criteria and constraints in a decision-making process using linear optimisation.
• Model specific scenarios as a linear optimisation problem.
• Apply linear programming to optimise a two variable linear optimisation problem.

How is the course structured?

• The course is not facilitated, but is designed to support peer learning through online discussions.
• The course is designed to last for two weeks but you can take longer to complete it.
• Each week is divided up into two activities.
• Each activity has a series of steps.
• There are quizzes, exercises and discussions for you to do in each activity.
• There is a graded assignment at the end of the course. You can take this assignment as many times as you like to get your Certificate of Achievement. The pass mark is 70%.

Maths!

Unsurprisingly, there is some maths in this course. You may know that maths is at the heart of computing science subjects so you’ll be doing some to give you an idea of the kinds of how maths is used in technology-assisted decision-making. We have made the exercises for these parts of the course optional, as you are not expected to know the maths, but for those of you who like a maths challenge, do give them a go! (You do not need to know the maths to pass the assignment and get your certificate).

What do you need to do next?

Work your way through the course, one step at a time. We only ask that you maintain your enthusiasm and work your way through all of the materials provided (video, reading, exercises, investigations, discussions) and join in with your fellow learners in the discussions – supporting and helping each other is at the heart of this course like this so please participate.