AI in Practice: Applying AI from edX

This course is not about difficult algorithms and complex programming; it is a course for anyone interested in learning how to integrate AI into their own organization.

To understand how current Artificial Intelligence applications can be successfully integrated in organizations, we look at different examples. For instance, how ING uses reinforcement learning for personalized dialog management with its customers or how Radboud UMC uses diagnostic image analysis to discover early stages of infectious diseases.

As part of our two-course program ‘AI in Practice’, this course will guide you in the practical aspects of applying AI in your own organization. You will examine typical applications of AI in use already and learn from their experience. These include challenges of implementation, lifecycle aspects, as well as the maintenance and management of AI applications.

The course presents a variety of case studies from actual situations in public organizations and private enterprises in the healthcare, financial, retail and telecommunications sectors. These include Radboud UMC, the Municipality of Amsterdam, ING, Ahold Delhaize and KPN.

‘AI in Practice – Applying AI’ gives you the ammunition to understand the practical aspects required for the implementation of a variety of AI applications in your organization.

This course has been developed by Delft University of Technology and the Innovation Center for Artificial Intelligence Academy (ICAI). ICAI is a national initiative involving industry, universities and government in the area of AI research and applications.

What's inside

Learning objectives

Describe the benefits and challenges of implementing ai in organizations, in terms of context, organizational background, problems, research approach and results.
Identify the conditions and requirements for the implementation of ai in terms of improvement strategies for organizations in industry, academia and education.
Understand the implementation aspects of ai and their significance for your own organization.

Write a plan for the application of ai in your own organization
After taking this course you will be able to:

Describe the benefits and challenges of implementing ai in organizations, in terms of context, organizational background, problems, research approach and results.
Identify the conditions and requirements for the implementation of ai in terms of improvement strategies for organizations in industry, academia and education.
Understand the implementation aspects of ai and their significance for your own organization.
Write a plan for the application of ai in your own organization
After taking this course you will be able to:

Syllabus

The course is built from five main topics on AI in Practice:

Reinforcement Learning for Real life - the AI for FinTech Research (ING and Delft University of Technology) and a Bonus Track of the Self-Learning Forecasting in Retail - the AI for Retail Lab Amsterdam (Ahold Delhaize and University of Amsterdam).

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores real-world applications of AI in healthcare, finance, retail, and telecommunications

Provides case studies from leading organizations to illustrate practical implementation of AI

Led by experts from Delft University of Technology and the Innovation Center for Artificial Intelligence Academy

Covers a range of topics, from reinforcement learning to diagnostic image analysis

Guides learners through the practical aspects of implementing AI in their organizations

Reviews summary

Practical ai for organizational application

According to students, 'AI in Practice: Applying AI' receives a largely positive reception, especially from those seeking to understand AI integration in organizations. Learners appreciate its practical approach, featuring real-world case studies from diverse sectors like finance and healthcare. The course is highly valued for its strategic and managerial focus, with guest lecturers providing invaluable industry insights. While it offers a strong high-level overview of AI applications, prospective learners should note it is less suited for deep technical or algorithmic understanding.

Helps learners develop plans for AI application in their own organizations.

"It gave me a good understanding of challenges and opportunities, and helped me develop a plan for my own organization."

"I gained actionable insights that helped me conceptualize and plan for AI projects within my workplace."

"The course truly equipped me with the practical understanding needed to apply AI in my real-world situation."

Features unique perspectives from guest lecturers in industry and academia.

"The guest lecturers offered unique perspectives from their real-world experience, which was a huge plus for me."

"I appreciated learning directly from people working on AI in companies like ING and Radboud UMC, providing practical insights."

"The course's case studies feature insights from actual situations with guest lecturers from ICAI labs, which I found very informative."

Offers a high-level, non-technical view for organizational leaders.

"I highly recommend this course for anyone interested in implementing AI solutions within an organization, focusing on strategic aspects."

"As a non-developer, this course was exactly what I needed to understand AI from a managerial perspective."

"It's an excellent overview for non-technical people, helping me understand the impact of AI in business."

Focuses on real-world AI implementation and challenges.

"The course excels in providing practical examples of AI use cases in various industries."

"I found the real-world case studies from companies like ING and Radboud UMC incredibly insightful and applicable."

"It gave me the ammunition to understand the practical aspects required for AI application in my own organization."

Some content is occasionally repetitive in its messaging.

"Sometimes it felt a bit repetitive in its messaging, but the core content on practical implementation was very strong."

"While generally excellent, there were a few instances where concepts seemed to be reiterated more than necessary, though not to the point of being a major issue."

Does not delve into complex algorithms or programming details.

"If I'm looking for deep technical knowledge, this isn't it, but for strategic insights, it's perfect."

"As a data scientist, I found some parts a bit too high-level, but the discussions on ethical implications were still valuable."

"I understand this course is not about difficult algorithms and complex programming, which some might find disappointing if they expect coding."

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 AI in Practice: Applying AI with these activities:

Review the principles of machine learning

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Revisit the basic principles of machine learning to ensure a strong foundation for the course material.

Browse courses on Machine Learning

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Re-read the course syllabus and lecture notes from previous courses on machine learning.
Work through a few practice problems on supervised and unsupervised learning.

Read "Artificial Intelligence: A Modern Approach"

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Gain a comprehensive understanding of the fundamental concepts and algorithms in AI.

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Read Chapter 1-3 to understand the history, applications, and basic concepts of AI.
Work through the exercises and problems at the end of each chapter.
Attend a book club or discussion group to discuss the key ideas in the book.

Complete the "AI for Everyone" Coursera specialization

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Gain practical experience with AI techniques through hands-on tutorials and projects.

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Enroll in the Coursera specialization.
Complete the introductory course and choose two or three elective courses that align with your interests.
Work through the hands-on exercises and projects in each course.

Four other activities

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Solve LeetCode problems on AI topics

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Strengthen your problem-solving skills and reinforce your understanding of AI algorithms.

Browse courses on Machine Learning

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Create an account on LeetCode.
Filter problems by topic and difficulty level.
Solve problems and review solutions to identify areas for improvement.

Join a study group or online forum

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Engage with peers to discuss course material, share knowledge, and ask questions.

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Join a study group or online forum dedicated to AI.
Participate in discussions, ask questions, and share your own insights.
Collaborate with other members on projects or assignments.

Develop a prototype AI application

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Apply your knowledge by building a practical AI application that solves a specific problem.

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Identify a problem that can be addressed using AI.
Choose an appropriate AI technique and gather the necessary data.
Train and evaluate the AI model.
Deploy the prototype application and collect feedback.

Attend AI meetups or conferences

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Connect with professionals in the field, learn about industry trends, and expand your professional network.

Browse courses on Machine Learning

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Identify upcoming AI meetups or conferences in your area.
Attend the events and engage with speakers, attendees, and exhibitors.
Follow up with interesting individuals and explore potential collaborations.

Career center

Learners who complete AI in Practice: Applying AI will develop knowledge and skills that may be useful to these careers:

AI in Health Care

**AI in Health Care** professionals use artificial intelligence to enhance patient care in a variety of ways. They may develop new AI-powered tools for disease diagnosis, treatment planning, or drug discovery. They may also work with clinicians to implement AI solutions into existing healthcare systems. This course will provide you with the knowledge and skills you need to develop AI solutions for this industry. You will have the opportunity to learn from experts in the field and apply your knowledge to real-world case studies.

See salaries and explore the career path for AI in Health Care

AI Trainer

**AI Trainers** work with engineers to help train Artificial Intelligence models. AI Trainers prepare the data used to train models, monitor the training process, and evaluate the performance of models. This course will help you develop the skills you need to become an AI Trainer. You will have the opportunity to learn about the different types of AI models, the techniques used to train them, and the tools used to evaluate them.

See salaries and explore the career path for AI Trainer

AI Engineer

**AI Engineers** design, develop, and implement AI solutions. They work with data scientists to identify the data that is needed to train AI models, and they work with software engineers to develop the code that implements the models. This course will provide you with the skills you need to become an AI Engineer. You will learn about the different types of AI models, the techniques used to train them, and the tools used to implement them.

See salaries and explore the career path for AI Engineer

AI Consultant

**AI Consultants** help businesses understand how AI can be used to improve their operations. They work with clients to identify the business problems that AI can solve, and they develop and implement AI solutions. This course will provide you with the knowledge and skills you need to become an AI Consultant. You will have the opportunity to learn about the different types of AI models, the techniques used to train them, and the tools used to implement them.

See salaries and explore the career path for AI Consultant

Data Scientist

**Data Scientists** use their knowledge of mathematics, statistics, and computer science to extract insights from data. They work with businesses to identify the data that is needed to solve business problems, and they develop and implement models to analyze the data. This course will help you develop the skills you need to become a Data Scientist. You will have the opportunity to learn about the different types of data analysis techniques, the tools used to perform data analysis, and the best practices for data visualization.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

**Machine Learning Engineers** design, develop, and implement machine learning models. They work with data scientists to identify the data that is needed to train machine learning models, and they work with software engineers to develop the code that implements the models. This course will provide you with the skills you need to become a Machine Learning Engineer. You will learn about the different types of machine learning models, the techniques used to train them, and the tools used to implement them.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

**Software Engineers** design, develop, and implement software applications. They work with engineers and other professionals to define the requirements for software applications and to develop and implement the applications. This course will help you develop the skills you need to become a Software Engineer. You will have the opportunity to learn about the different types of software applications, the techniques used to develop them, and the tools used to implement them.

See salaries and explore the career path for Software Engineer

Computer Vision Engineer

**Computer Vision Engineers** work with engineers to develop computer vision models to solve problems in a variety of industries, such as manufacturing, healthcare, and transportation. This course will help you develop the skills you need to become a Computer Vision Engineer. You will have the opportunity to learn about the different types of computer vision models, the techniques used to train them, and the tools used to implement them.

See salaries and explore the career path for Computer Vision Engineer

Natural Language Processing Engineer

**Natural Language Processing Engineers** work with engineers to develop natural language processing models to solve problems in a variety of industries, such as customer service, marketing, and finance. This course will help you develop the skills you need to become a Natural Language Processing Engineer. You will have the opportunity to learn about the different types of natural language processing models, the techniques used to train them, and the tools used to implement them.

See salaries and explore the career path for Natural Language Processing Engineer

Robotics Engineer

**Robotics Engineers** work with engineers to develop robots that can perform a variety of tasks, such as manufacturing, healthcare, and food preparation. This course will help you develop the skills you need to become a Robotics Engineer. You will have the opportunity to learn about the different types of robots, the techniques used to develop them, and the tools used to implement them.

See salaries and explore the career path for Robotics Engineer

Project Manager

**Project Managers** plan, organize, and execute projects. They work with stakeholders to define the goals of a project and to develop a plan to achieve those goals. This course will help you develop the skills you need to become a Project Manager. You will have the opportunity to learn about the different phases of a project, the tools used to manage projects, and the best practices for project management.

See salaries and explore the career path for Project Manager

Business Analyst

**Business Analysts** work with businesses to identify and solve business problems. They work with stakeholders to define the requirements for a solution and to develop a plan to implement the solution. This course will help you develop the skills you need to become a Business Analyst. You will have the opportunity to learn about the different types of business problems, the techniques used to solve them, and the tools used to implement solutions.

See salaries and explore the career path for Business Analyst

Data Analyst

**Data Analysts** use their knowledge of mathematics, statistics, and computer science to analyze data and to identify trends and patterns. This course will help you develop the skills you need to become a Data Analyst. You will have the opportunity to learn about the different types of data analysis techniques, the tools used to perform data analysis, and the best practices for data visualization.

See salaries and explore the career path for Data Analyst

UX Designer

**UX Designers** work with engineers and other professionals to design the user experience for software applications. They work with stakeholders to define the requirements for the user experience and to develop a plan to implement the experience. This course will help you develop the skills you need to become a UX Designer. You will have the opportunity to learn about the different aspects of user experience design, the tools used to design user experiences, and the best practices for user experience design.

See salaries and explore the career path for UX Designer

Technical Writer

**Technical Writers** develop and write documentation for software applications and other technical products. They work with engineers and other professionals to define the requirements for the documentation and to develop a plan to implement the documentation. This course will help you develop the skills you need to become a Technical Writer. You will have the opportunity to learn about the different types of technical documentation, the tools used to develop technical documentation, and the best practices for technical writing.

See salaries and explore the career path for Technical Writer