Module 2 Prompt Engineering Lab
Course Description
Prompt Engineering and AI Strategy is designed to equip business professionals, managers, and technical staff with practical skills in prompt engineering and AI strategy. Attendees will learn how to identify high-impact AI opportunities, align AI initiatives with business goals, and create effective prompts for generative AI tools. The course combines theory with real-world scenarios and interactive activities to ensure immediate application to daily work. Key topics include prompt engineering fundamentals, advanced prompting techniques, use case discovery, impact-complexity mapping, responsible AI principles, and AI governance. By the end of this course, participants will be able to:
- Understand Prompt Engineering: Explain what prompt engineering is, why it matters, and how it enables effective use of generative AI tools in business context.
- Apply Prompt Components: Identify and use the four key components of a prompt (Instructions, Context, Input Data and Output Indicator) to achieve clear and relevant responses.
- Use Advanced Prompting Techniques: Demonstrate how to apply zero-shot, few-shot, and chain-of-thought prompting to solve a variety of business problems.
- Design Business Ready Prompts: Identify and prioritise high-impact AI use cases using frameworks like the Impact-Complexity Matrix and ICE scoring.
- Map AI Use Cases: Complete an AI opportunity Canvas to articulate business value, data reqirements, and implementation challenges for selected use cases.
- Assess Organisational Readines: Evaluate technology infrastructure, data quality, and integration needs to support successful AI adoption.
- Embed Responsible AI Principles: Recognise and apply principles of fairness, transparency, accountability, and privacy in AI solution design and deployment.
- Collaborate and Iterate: Work in teams to build, review, and improve prompts, encouraging a culture of continuous learning and peer feedback.
- Reflect on Real-World Case Studies: Analyse success factors and pitfalls in AI adoption through discussion of practical examples.
Course Structure
1. Prompt Engineering Fundamentals
- What is prompt engineering and why is it important?
- The four components of an effective prompt: Instructions, Context, Input Data, Output Indicator
- Role prompting and task-specific prompt structures
- Zero-shot, few-shot, and chain-of-though prompting
- Meta prompting and use of delimiters
- Task decomposition for complex operations
- How to create high quality prompts
- Hands-on: Crafting and refining prompts for business scenarios
- Introduction to design thinking for AI transformation
- Group activity: Identify business pains points and opportunities
- Explore how AI can reshape business models and processes
- Case studies and examples of high-impact AI use cases
- Group Activity: Brainstorm and prioritise AI use cases for business functio
- Group Activity: Score each use case and map on the Impact-Complexity Matrix
- Building AI literacy and confidence in teams
- Strategies for driving adoption and overcoming resistance
- Role of champions and peer learning
- Using AI to streamline workflows and reduce manual effort
- Mapping operational processes to identify automation opportunities
- Human-in-the-loop vs. Human-on-the-loop
- Technology infrastructure and scalable AI
- Data quality: dimensions and management approaches
- Evaluating build vs. buy options for AI solutions
- Responsible AI principles: fairness, transparency, accountability, privacy
- Governance frameworks and controls for ethical AI use
- Managing risks, compliance, and data privacy
- Group Activity: Use Case Prioritisation using the ICE (Impact, Confidence, Effort) model
- Overview of practical tools and frameworks for AI project planning and prioritisation
- How to strengthen AI adoption with sample metrics for measuring AI success across business functions
- Highlight importance of innovation champions and their roles
2. Advanced Prompting Techniques
3. Design Thinking Sprint – FinServ Ltd Case Study
4. Reimagining Business with AI
5. Empowering People
6. Optimising Operations
7. Building the Right Tech Foundation
8. Governing AI Responsibly
9. AI Strategy Toolkit
Should Attend
This course is designed for:
- Business Leaders and Managers: Individuals responsible for driving digital transformation, improving team productivity, and making strategic decisions about AI adoption.
- ICT Professionals and Analysts: Those who manage data, workflows, or business processes and want to leverage AI-powered tools to streamline operations and enhance reporting.
- General Staff and Knowledge Workers: Anyone who uses digital tools in their daily work and wants to boost efficiency, creativity, and collaboration through AI.
- Innovation Champions and Early Adopters: Employees nominated to lead AI initiatives or those keen to support colleagues in adopting new technologies.
- Project Owners and Change Agents: Professionals tasked with identifying business pain points, mapping opportunities, and implementing process improvements.
- HR, Operations, Finance, and Marketing Team: Functional experts seeking to optimise workflows, automate routine tasks, and measure the impact of AI on their business area.
- Anyone Interested in AI Literacy: Staff looking to build foundational knowledge in prompt engineering, responsible AI, and practical application of generative AI in the workplace
Prerequisites
No prior experience with AI or prompt engineering is required. The course is suitable for both technical and non-technical participants, and all necessary tools and access will be provided for hands-on learning.
Assessment
There is no assessment. At the end of the sessions you will receive a Certificate of Attendance.
Key-Features
1. Practical, Scenario-Based Exercises
- Participants engage in hands-on activities focused on designing, structuring, and refining prompts, mapping AI use cases, and applying strategic frameworks to real-world business scenarios.
2. Real-World Business Scenarios
- This course is built around authentic use cases, such as process automation, data analysis, and communication, tailored for business leaders, ICT professionals, and functional teams
3. Advanced Prompt Engineering Techniques
- Attendees will learn how to create high-quality prompts using zero-shot, few-shot, chain-of-though, and meta prompting, with practical tips for structuring and refining prompts for different business needs.
4. Group Activities and Collaborative Learning
- Interactive group activities (design thinking sprints, use case mapping, and prioritisation exercises) to encourage peer learning, feedback, and real-time application of concepts.
5. Responsible AI and Governance
- This course covers responsible AI principles, risk management, and governance frameworks, helping participants understand compliance, data privacy, and ethical considerations in AI adoption.
6. Immediate Application to Daily Work
- Attendees are encouraged to apply prompt engineering and AI strategy tools to their own workflows, with practical guidance for integrating AI into daily routines and driving adoption within their organisations.
7. Feedback and Continuous Improvement
- The course includes opportunities for participants to provide feedback, share experiences, and learn from each other, fostering a culture of continuous improvement and innovation.
Course Structure
1. Prompt Engineering Fundamentals
- What is prompt engineering and why is it important?
- The four components of an effective prompt: Instructions, Context, Input Data, Output Indicator
- Role prompting and task-specific prompt structures
- Zero-shot, few-shot, and chain-of-though prompting
- Meta prompting and use of delimiters
- Task decomposition for complex operations
- How to create high quality prompts
- Hands-on: Crafting and refining prompts for business scenarios
- Introduction to design thinking for AI transformation
- Group activity: Identify business pains points and opportunities
- Explore how AI can reshape business models and processes
- Case studies and examples of high-impact AI use cases
- Group Activity: Brainstorm and prioritise AI use cases for business functio
- Group Activity: Score each use case and map on the Impact-Complexity Matrix
- Building AI literacy and confidence in teams
- Strategies for driving adoption and overcoming resistance
- Role of champions and peer learning
- Using AI to streamline workflows and reduce manual effort
- Mapping operational processes to identify automation opportunities
- Human-in-the-loop vs. Human-on-the-loop
- Technology infrastructure and scalable AI
- Data quality: dimensions and management approaches
- Evaluating build vs. buy options for AI solutions
- Responsible AI principles: fairness, transparency, accountability, privacy
- Governance frameworks and controls for ethical AI use
- Managing risks, compliance, and data privacy
- Group Activity: Use Case Prioritisation using the ICE (Impact, Confidence, Effort) model
- Overview of practical tools and frameworks for AI project planning and prioritisation
- How to strengthen AI adoption with sample metrics for measuring AI success across business functions
- Highlight importance of innovation champions and their roles
2. Advanced Prompting Techniques
3. Design Thinking Sprint – FinServ Ltd Case Study
4. Reimagining Business with AI
5. Empowering People
6. Optimising Operations
7. Building the Right Tech Foundation
8. Governing AI Responsibly
9. AI Strategy Toolkit
Should Attend
This course is designed for:
- Business Leaders and Managers: Individuals responsible for driving digital transformation, improving team productivity, and making strategic decisions about AI adoption.
- ICT Professionals and Analysts: Those who manage data, workflows, or business processes and want to leverage AI-powered tools to streamline operations and enhance reporting.
- General Staff and Knowledge Workers: Anyone who uses digital tools in their daily work and wants to boost efficiency, creativity, and collaboration through AI.
- Innovation Champions and Early Adopters: Employees nominated to lead AI initiatives or those keen to support colleagues in adopting new technologies.
- Project Owners and Change Agents: Professionals tasked with identifying business pain points, mapping opportunities, and implementing process improvements.
- HR, Operations, Finance, and Marketing Team: Functional experts seeking to optimise workflows, automate routine tasks, and measure the impact of AI on their business area.
- Anyone Interested in AI Literacy: Staff looking to build foundational knowledge in prompt engineering, responsible AI, and practical application of generative AI in the workplace
Prerequisites
No prior experience with AI or prompt engineering is required. The course is suitable for both technical and non-technical participants, and all necessary tools and access will be provided for hands-on learning.
Assessment
There is no assessment. At the end of the sessions you will receive a Certificate of Attendance.
Key-Features
1. Practical, Scenario-Based Exercises
- Participants engage in hands-on activities focused on designing, structuring, and refining prompts, mapping AI use cases, and applying strategic frameworks to real-world business scenarios.
2. Real-World Business Scenarios
- This course is built around authentic use cases, such as process automation, data analysis, and communication, tailored for business leaders, ICT professionals, and functional teams
3. Advanced Prompt Engineering Techniques
- Attendees will learn how to create high-quality prompts using zero-shot, few-shot, chain-of-though, and meta prompting, with practical tips for structuring and refining prompts for different business needs.
4. Group Activities and Collaborative Learning
- Interactive group activities (design thinking sprints, use case mapping, and prioritisation exercises) to encourage peer learning, feedback, and real-time application of concepts.
5. Responsible AI and Governance
- This course covers responsible AI principles, risk management, and governance frameworks, helping participants understand compliance, data privacy, and ethical considerations in AI adoption.
6. Immediate Application to Daily Work
- Attendees are encouraged to apply prompt engineering and AI strategy tools to their own workflows, with practical guidance for integrating AI into daily routines and driving adoption within their organisations.
7. Feedback and Continuous Improvement
- The course includes opportunities for participants to provide feedback, share experiences, and learn from each other, fostering a culture of continuous improvement and innovation.
Register Your Interest: