Introduction to Technology-Assisted Decision-Making (Coursera)

Introduction to Technology-Assisted Decision-Making (Coursera)
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Introduction to Technology-Assisted Decision-Making (Coursera)
Technology-assisted decision-making is increasingly important to modern businesses in a wide variety of fields, including finance, healthcare, marketing, and logistics, among others. It introduces speed and efficiency because substantial amounts of data can be processed efficiently to enable faster, objective, contextual decisions. This online course will introduce you to the fundamental concepts of technology-assisted decision-making and its diverse applications in resource allocation, production planning, transportation, scheduling, and network optimisation.

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You will learn to formulate optimisation problems as mathematical models and apply diverse techniques for their resolution using specialised software.

You'll learn to apply powerful techniques such as linear programming and optimisation algorithms on graphs, gaining practical skills for real-world problem-solving.

By the end of the course, you'll be well-prepared to apply these skills across diverse fields and embark on future studies or careers in data-driven decision-making.

Click Start, a nationwide training programme designed to help young people develop digital skills, offers this course. Click Start offers scholarships giving free access to young people in the UK. Follow the link in the Click Start icon on the top, to check if you are eligible for free access!


What you'll learn

- Describe the concept of technology-assisted decision-making and the associated terminology within the field.

- Demonstrate the ability to formulate optimisation problems as mathematical models and apply diverse techniques for their resolution.

- Understand the applications of optimisation including resource allocation, production planning, transportation, scheduling, and network optimisation.


Syllabus


Week 1: Decision-making with graph theory

Hello and welcome to 'An Introduction to Technology-Assisted Decision-Making.' Humans make decisions all the time, but do we always make the best ones? If technology could enhance decision-making processes across various aspects of life, from healthcare to manufacturing, could a society guided by advanced algorithms redefine the boundaries of human choice in a positive way? This course introduces the concept of technology-assisted decision-making. You will learn about a variety of techniques used to help optimise the best outcomes in industry, health and education. It covers topics such as identifying decision-making problems, formulating optimisation problems, developing mathematical models, and using specialised software to solve them. In this first week of the course, you will learn what is meant by 'technology-assisted decision-making'. You will be introduced to our first example of how technology, and computer science, can be used to support decision-making using a practical example. You will then explore a topic in computer science called 'graph theory' and how it can be applied to the practical example to solve a problem. Let's get started!


Week 2. Decision-making with linear programming

This week, you will be learning about a second type of technology-assisted decision-making, namely linear optimisation. Linear programming and optimisation are powerful techniques used in technology-assisted decision-making to find the best possible solution to a problem within a set of constraints. Linear programming involves optimising a linear objective function, subject to linear inequality or equality constraints. It is used to make decisions that involve allocating resources, such as determining the most efficient production plan, or allocating staff to various departments while minimising costs. Don't worry if you don't understand what this means - you will at the end of the week!



MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Course Auditing
44.00 EUR
No prior experience required

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.