Find an education provider in Generative AI

Generative AI (Prompt engineering) Education Partners

This page will show the various Accredited Education Partners, that are allowed to provide Ai an/or Data (EDF) related trainings. And which have been qualified to meet the required quality norms of EDF and/or the Dutch AI Coalition and can provide qualative training in the related subjects.

What is a Generative AI Fundamentals training?

Course title:

– ChatGPT for Business Course
– Certified Generative AI Fundamentals based on ChatGP 

Course Description: 

 The Certified Generative AI Fundamentals course is designed to give business people with a non-technical background a comprehensive understanding of ChatGPT, one of the most powerful AI language models available in the market today. The course will delve into how ChatGPT differs from other chatbots and explore its language generation abilities, as well as the field of natural language processing (NLP). You get a look behind the scene showing how ChatGPT is built.  

When the basics are clear, we will jump into the skill of prompt engineering, including the 4 rules of working with generative AI and a 5-question framework to write a good prompt. You will explore various business use cases and best practices for selecting the right tools, and guidelines for employees, and how to integrate ChatGPT into existing workflows. 

The course will also cover the limitations and risks associated with ChatGPT, such as bias and privacy concerns, as well as the potential for misuse. You will learn how to mitigate these risks using business guidelines and ethical considerations. 

Throughout the course, students will have hands-on experience working with ChatGPT and learn how to apply it to real-world business problems. You will gain practical knowledge about how to use ChatGPT effectively and develop critical thinking skills to evaluate its potential in various business use cases. By the end of the course, you will be able to confidently identify and implement ChatGPT in their business. 

Target audience:  

The target audience for a Certified Generative AI Fundamentals course would be business professionals and leaders with a non-technical background who are interested in leveraging the power of AI language models like ChatGPT to enhance their business operations. This may include individuals in roles such as marketing, sales, customer support, product management, and executive leadership. The course is designed to provide a comprehensive understanding of ChatGPT and its capabilities, as well as best practices for integrating it into existing workflows and mitigating risks associated with its use. 

Learning objectives:  

Upon completion of this course, learners will be able to: 

  • Understand the fundamentals of generative AI and natural language processing (NLP). 
  • Gain an introduction to ChatGPT, its architecture, and its language generation abilities. 
  • Differentiate ChatGPT from other chatbots and comprehend its supervised model, human reinforcement learning, and proxity model. 
  • Apply ChatGPT to various business use cases, utilizing the 4 rules of working with generative AI and the 5-question framework to write a good prompt. 
  • Integrate ChatGPT into existing workflows and evaluate its potential in various business scenarios. 
  • Recognize the limitations, risks, and ethical considerations associated with ChatGPT and apply business guidelines and ethical principles to mitigate them. 


  1. Fundamentals 
    1. Introduction to ChatGPT   
    2. Understanding NLP, and ChatGPT’s language Generation abilities. 
    3. How does ChatGPT differs from other chatbots? 
  1. ChatGPT Architecture 
    1. Supervised model 
    2. Human reinforcement learning 
    3. Proxitymodel 
  1. Applying ChatGPT 
    1. 4 rules of working with generative AI 
    2. 5- question framework to write a good prompt. Including testing and itering. 
  1. Integration of ChatGPT 
    1. Critical thinking of ChatGPT business cases 
    2. Ways to integrate ChatGPT in workflows.  
  1. Limitations, Risks and business guidelines  
    1. Limitations, risks and business guidelines 
    2. Ethical guidelines and law 
Extra information 

In this section, you can read about how the ChatGPT Exam is structured and which subjects you will be tested on as a candidate. It is also a tool that you can use to prepare yourself for the test. 

In this syllabus we indicate the topics which are covered in the exam and additional topics which are relevant for further study but not covered in the exam. During the exam you will be tested on your general knowledge about: 

Section 1: Fundamentals 

Background introduction of ChatGPT, and how it evolved into a game-changer technology.  

  1. Introduction to ChatGPT: This module covers the basic introduction to ChatGPT, its capabilities, and potential applications in business.

 Describes the history of ChatGPT. How researchers have been developing language models over the years, and how this has led to ChatGPT. Explain the earlier success of GPT-2 and GPT-3 models, which made headlines for their advanced language generation capabilities and made the way to ChatGPT. Describe the important role of deep learning in these developments. Participants need to do a Use Case Identification Assessment. 

2. Understanding NLP and ChatGPT’s language generation abilities: This module covers the basics of natural language processing (NLP) and how ChatGPT generates human-like responses.

Understand the hierarchy in Artificial Intelligence, Machine Learning and Natural Language processing, and how they relate to each other. Explain the different methods of Machine learning and understand where ChatGPT is positioned. Describe the fundamentals of natural language processing and how ChatGPT utilizes NLP to generate human-like responses. 

 3. How does ChatGPT differ from other chatbots? This module covers the differences between ChatGPT and other available chatbots.


Name the unique features that set ChatGPT apart from other chatbots in the market. Understand the potentials and the limitations of rule-based chatbots and their inability to handle complex, nuanced responses. Describe that ChatGPT utilizes machine learning to generate human-like responses that can adapt to various scenarios.  

Section 2: The ChatGPT Architecture 

Introduces the different machine learning methods of the ChatGPT model, and gives an overview of the added value of each method. Highlights which types of models address which types of problems. 


  1. 4. Model 1 – Supervised model. This models covers how this learning method works, and it’s role in the ChatGPT


Describe how the Supervised model is used to train ChatGPT on large amounts of text data with human annotations to learn how to generate responses based on context. Explain how ChatGPT uses a transformer-based neural network architecture to learn the patterns and relationships between words and phrases. 



  1. 5. Model 2 – Human reinforcement learning. This models covers how this learning method works, and it’s role in the ChatGPT


Describe how Human reinforcement learning is another type of machine learning where an AI model learns from feedback given by humans in order to improve its performance.  Explain the rating system behind this model and the essential role of the human reinforcement learning on top of learning on large amounts of data.  


  1. 6. Model 3 – Proximal Policy Optimization (PPO) model. This models covers how this learning method works, and it’s role in the ChatGPT


Understand how PPO is a form of the machine learning method ‘reinforcement learning’. Describe the role Proximal Policy Optimization (PPO) model in the ChatGPT model.  Explain how the PPO model adds value in combination with the supervised model and the human reinforcement model in the learning process of ChatGPT. 

 Section 3: Applying ChatGPT / Prompt-engineering 

 4 rules of working with Generative AI 

 Understand the lack of judgment and explain the importance of common sense and plain, idiom-free language prompts with clear instructions to help the AI understand and perform the task correctly. Describe input types, datasets, and how the quality of these input data result in high-quality outcomes. Understand the imperfection of the model and consistently need of monitoring and adjusting the prompts to get better results. 

 5- question framework to write a good prompt. Including testing and itering.


Describes a basic approach towards building a prompt suited for ChatGPT. The 5-question framework described highlighting the input that should be involved and raising awareness of specification at each step of the prompt-creating process. Highlight pitfalls including personal information, company information, and bias. Describe the use of the 5-question framework, and what each question entails.  


Participants will be assessed based on their ability to generate effective custom prompts for different business use cases, as well as their ability to tailor the tone and style of the prompts to fit the brand and messaging. The participants should be able to build and improve prompts based on the elements of who, what, where, why and how. Participants need to do a Prompt Writing Assessment.  

Section 4 Integration of ChatGPT in your business 


  1. Critical thinking of Business cases

Describes a range of applications of ChatGPT within your business, how these applications impact business. Participants need to do a Use Case Identification Assessment. 


  1. Ways to integrate ChatGPT in workflows 

Describe various scenarios of integrating ChatGPT in your workflow highlighting the steps involved and raising awareness of the business context and trustworthiness assessment at each scenario. Participants need to argument which scenario is suited in which business context.  



Section 5:  Limitations, Risks and ethical guidelines 


  1. Limitations & Risks 


Addresses the limitations, risks and with ChatGPT. Describe why you should not 100% trust the outcome, and why a human check is mandatory. Line out guidelines that a company can embrace to support the safe use of the technology. The importance of GDPR, and data policy. Emphasize the risks that arise in data and their impact on trustworthiness. 


  1. Ethical and business guidelines.  


Addresses ethical dilemmas associated with AI including the need for explainable AI. Introduce EU Ethical Guidelines and the need to maintain the trust of society in the use of AI.