University of Leeds - Introduction to Technology-Assisted Decision-Making
- Offered byCoursera
Introduction to Technology-Assisted Decision-Making at Coursera Overview
Duration | 8 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Introduction to Technology-Assisted Decision-Making at Coursera Highlights
- Earn a certificate of completion
- Add to your LinkedIn profile
Introduction to Technology-Assisted Decision-Making at Coursera Course details
- 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.
- 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. 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!
Introduction to Technology-Assisted Decision-Making at Coursera Curriculum
Week 1: Decision-making with graph theory
About the course and its creator
Kruskal's algorithm
Welcome to An Introduction to Technology-Assisted Decision-Making
Lesson 1: Overview
What is is technology-assisted decision-making used for?
Introducing two key techniques
Lesson 2: Overview
Introducing GigaFibre
What are GigaFibre's plans for growth?
Exercise: planning GigaFibre's network
Solution: planning GigaFibre's network
Lesson 2: Summary and next steps
Lesson 3: Overview
An introduction to graph theory
The minimum spanning tree problem
Applying Kruskal's algorithm to the GigaFibre scenario
Exercise: Kruskal's algorithm: Yorkshire
Solution: Kruskal's algorithm: Yorkshire
Exercise: Gigafibre in Lincolnshire and Yorkshire
Solution: GigaFibre in Lincolnshire and Yorkshire
Optional: Is Kruskal's algorithm correct?
Lesson 3: Summary
Checking your understanding of graph theory
Say hello to your fellow learners
How could technology-assisted decision-making be used?
GigaFibre: are there other considerations?
How did it go?
Week 2. Decision-making with linear programming
The bakery problem
An introduction to Geogebra
The bakery problem solution
Lesson 4: Overview
What is linear optimisation?
The bakery problem
The bakery problem: formulation
The bakery problem solution: the feasible region
Optional: Have a go at using Geogebra
Explaining the bakery problem solution using the graphical method
Lesson 4: Summary and next steps
Lesson 5: Overview
Linear programming: Give it a go
Give it a go: solution
Optional: teach it!
Optional: Minimisation problems
Optional: Variants on optimisation
Lesson 5: Summary and next steps
Course summary
Further study
Test your understanding and get your certificate
Applying the graphical method
Optional: Teach it! discussion
Reflecting on the course together
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