Introduction to Technology-Assisted Decision-Making from 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.

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's inside

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!

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores graph theory, which is applied in AI and problem-solving

Teaches linear programming, which is vital for resource allocation

Examines optimisation algorithms on graphs, which is in-demand in industry

Develops skills for problem-solving using technology, which is valuable in various domains

Requires proficiency in computer science and mathematics, which may not be suitable for complete beginners

Taught by instructors from industry, which provides practical insights

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Technology-Assisted Decision-Making with these activities:

Review Algebra

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Algebra is needed to understand optimizing algebraic expressions.

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Review basic algebraic operations.
Solve practice problems.

Solve graph theory problems

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Practicing graph theory problems will help you develop your problem-solving skills and gain a deeper understanding of the concepts covered in the course.

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Identify a graph theory problem.
Analyze the problem and identify the relevant concepts.
Develop a solution strategy.
Implement the solution strategy.
Test and evaluate the solution.

Find a mentor in the field of data-driven decision-making

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A mentor can provide guidance and support.

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Identify potential mentors.
Reach out to the mentors and express your interest.
Meet with the mentors to discuss your goals.

Seven other activities

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Practice applying linear programming techniques

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Solving practice problems will help you master the techniques and algorithms covered in the course, improving your problem-solving skills in decision-making.

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Identify a problem that can be solved using linear programming.
Formulate the problem as a mathematical model.
Solve the model using a linear programming solver.
Analyze the results and make recommendations.

Follow tutorials for linear programming

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Supplemental tutorials can help you solidify concepts.

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Search for tutorials on linear programming.
Follow the steps in the tutorials.

Attend a networking event focused on data-driven decision-making

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Connect with professionals in the field.

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Find a relevant networking event.
Attend the event.
Introduce yourself to people.
Discuss your interests and career goals.

Practice modeling problems with linear programming

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Practice is essential to master this subject.

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Find practice problems.
Solve the problems using linear programming methods.
Review your solutions.

Attend a workshop on optimization techniques

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Workshops offer hands-on experience.

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Find a relevant workshop.
Register for the workshop.
Attend the workshop.
Participate in the exercises.

Develop an optimization model for a real-world problem

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Apply your skills to a real-world scenario.

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Identify a problem that can be solved using linear programming.
Develop a mathematical model for the problem.
Solve the model using a software tool.
Analyze the results.
Present your findings.

Develop a decision-making model for a real-world problem

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Applying the concepts from the course to a real-world problem will help you develop your decision-making skills and gain hands-on experience in solving complex problems.

Browse courses on Decision-Making

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Identify a real-world problem that requires decision-making.
Gather data and information about the problem.
Develop a decision-making model using the concepts covered in the course.
Test and evaluate the model.
Present the model and your findings to stakeholders.

Career center

Learners who complete Introduction to Technology-Assisted Decision-Making will develop knowledge and skills that may be useful to these careers:

Operations Research Analyst

Operations Research Analysts use technology to make decisions about how to allocate resources most efficiently. This course can help you develop the skills you need to be an Operations Research Analyst by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as an Operations Research Analyst.

See salaries and explore the career path for Operations Research Analyst

Data Scientist

Data Scientists use technology to collect and analyze data, and to develop decision-making models. This course can help you develop the skills you need to be a Data Scientist by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Data Scientist.

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Management Consultant

Management Consultants use technology to help businesses make better decisions. This course can help you develop the skills you need to be a Management Consultant by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Management Consultant.

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Financial Analyst

Financial Analysts use technology to analyze financial data and make investment decisions. This course can help you develop the skills you need to be a Financial Analyst by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Financial Analyst.

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Business Analyst

Business Analysts use technology to analyze business data and make decisions about how to improve operations. This course can help you develop the skills you need to be a Business Analyst by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Business Analyst.

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Software Engineer

Software Engineers design and develop software systems. This course can help you develop the skills you need to be a Software Engineer by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Software Engineer.

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Data Engineer

Data Engineers design and build systems for collecting, storing, and analyzing data. This course can help you develop the skills you need to be a Data Engineer by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Data Engineer.

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Systems Engineer

Systems Engineers design and build complex systems. This course can help you develop the skills you need to be a Systems Engineer by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Systems Engineer.

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Industrial Engineer

Industrial Engineers design and improve production and manufacturing systems. This course can help you develop the skills you need to be an Industrial Engineer by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as an Industrial Engineer.

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Transportation Engineer

Transportation Engineers design and build transportation systems. This course can help you develop the skills you need to be a Transportation Engineer by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Transportation Engineer.

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Logistics Engineer

Logistics Engineers design and manage supply chains. This course can help you develop the skills you need to be a Logistics Engineer by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Logistics Engineer.

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Operations Manager

Operations Managers oversee the daily operations of a business. This course can help you develop the skills you need to be an Operations Manager by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as an Operations Manager.

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Project Manager

Project Managers plan and execute projects. This course can help you develop the skills you need to be a Project Manager by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Project Manager.

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Product Manager

Product Managers oversee the development and launch of new products. This course can help you develop the skills you need to be a Product Manager by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Product Manager.

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Marketing Manager

Marketing Managers oversee the marketing and advertising of a company's products or services. This course can help you develop the skills you need to be a Marketing Manager by teaching you how to use linear programming and optimisation algorithms to solve problems. You will learn how to use technology to collect and analyze data, and how to develop decision-making models. This course can help you build a strong foundation for a career as a Marketing Manager.

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