Generative AI Intermediate Prompting Training in Stockholm

This course provides a practical and accessible introduction to generative AI, focusing on how modern AI systems create content, support decision-making, and enable new ways of working across organisations. Learners will explore the capabilities of generative AI, understand how it differs from traditional AI approaches, and assess both the opportunities and risks associated with its adoption.

The course emphasises real-world relevance, helping learners evaluate where generative AI can deliver business value and how it can be implemented responsibly. Through examples, discussion, and hands-on interaction with generative AI tools, participants will build the confidence to engage with these technologies effectively and apply learning back to their organisational context.

This course is designed to be accessible to a wide audience and does not require deep technical expertise. Learners should have:

• A general awareness of digital technologies used in modern organisations.
• An interest in understanding how AI is influencing business, roles, and decision-making.
• No prior experience with AI development, data science, or programming is required.

Target audience

This course is suitable for learners who want a foundational understanding of generative AI and its business impact, including:

• Beginners and intermediate learners exploring generative AI concepts for the first time.
• Professionals across industries such as business operations, marketing, HR, education, healthcare, and technology.
• Managers, team leaders, and individual contributors who will share insights with their teams or influence AI adoption decisions.
• Organisations seeking to build a shared understanding of generative AI across multiple functions.

By the end of this course, learners will be able to:

• Describe the core capabilities of generative AI and the types of content it can create, including text, images, audio, video, and code.
• Explain the key differences between traditional AI systems and generative AI models.
• Analyse the strengths, limitations, and risks associated with generative AI in organisational settings.
• Evaluate real-world use cases and assess the feasibility of implementing generative AI across different industries.
• Interact with generative AI tools effectively using structured prompting techniques.
• Explain the concept of retrieval augmented generation and its value in improving accuracy and relevance for business use cases.

Introduction to generative AI
This module establishes a shared foundation for understanding generative AI and its growing influence.

• Overview of artificial intelligence and the evolution toward generative models.
• Capabilities and applications of generative AI across text, images, music, video, and code.
• Key differences between traditional AI approaches and generative AI systems.
• Demonstrations of commonly used generative AI tools and platforms.

Strengths and challenges of generative AI
This module explores both the potential and the limitations of generative AI to support informed decision-making.

• Strengths and benefits of generative AI, including productivity, creativity, and scalability.
• Common limitations such as hallucinations, bias, data dependency, and lack of transparency.
• Ethical, legal, and security considerations when using generative AI.
• Risks associated with misuse, overreliance, and poor governance.

Real-world applications and implementation of generative AI
This module focuses on how generative AI is applied in practice and how organisations can approach adoption.

• Industry use cases across marketing, healthcare, education, customer service, and technology.
• Evaluating business problems that generative AI can realistically address.
• Stakeholder considerations, including leadership, employees, customers, and regulators.
• Assessing feasibility, readiness, and strategic options for implementation.

Effective prompt design and retrieval augmented generation
This module develops practical skills for interacting with generative AI tools effectively.

• The significance of prompt design in shaping AI outputs.
• Core principles of clear, structured, and context-aware prompting.
• Common prompting strategies for business and professional use cases.
• Introduction to retrieval augmented generation and how it improves reliability and relevance.
• Understanding the business value of combining internal data with generative AI models.

Exams and assessments

There are no formal exams included in this course. Learners will complete informal knowledge checks, discussions, and practical activities throughout the course to reinforce understanding and support applied learning.

Hands-on learning

This course includes opportunities for experiential learning, including:

• Guided interaction with generative AI tools to create and refine outputs.
• Practical exercises focused on prompt design and evaluation of results.
• Scenario-based discussions exploring real organisational challenges and use cases.