Global Learning for Operational Leaders
Classroom
0 sessionsOnline / Live
0 sessionsIntroduction
Course overview
Why Attend
Prompt Engineering has become a critical skill for professionals seeking to maximize the value of Artificial Intelligence and Large Language Models (LLMs). This course provides participants with a practical understanding of how AI models work, how to design effective prompts, and how to apply advanced prompting techniques to improve accuracy, productivity, creativity, and decision-making across a variety of business and technical applications.
Course Methodology
The course combines interactive presentations, hands-on workshops, practical exercises, AI demonstrations, group discussions, prompt design labs, real-world case studies, and project-based learning to ensure practical application of prompt engineering techniques.
Course Objectives
By the end of this course, participants will be able to:
- Understand the fundamentals of Large Language Models (LLMs) and Generative AI
- Design effective prompts for a variety of business and technical applications
- Apply advanced prompt engineering techniques to improve AI outputs
- Evaluate and optimize prompt performance using structured methods
- Reduce inaccuracies, ambiguity, and repetitive responses
- Utilize prompt frameworks and reusable prompt templates
- Apply prompt engineering to content creation, analysis, automation, and decision support
Target Audience
- AI and digital transformation professionals
- Business analysts and consultants
- IT professionals and developers
- Data and innovation specialists
- Content creators and knowledge workers
- Project managers and business leaders
- Anyone seeking to leverage Generative AI tools effectively
Target Competencies
- Prompt engineering
- Generative AI applications
- AI-assisted decision-making
- Content generation and automation
- Critical thinking and problem-solving
- AI governance awareness
- Digital innovation
- Productivity enhancement
What you will achieve
Learning objectives
- Understand the fundamentals of Large Language Models (LLMs) and Generative AI
- Design effective prompts for a variety of business and technical applications
- Apply advanced prompt engineering techniques to improve AI outputs
- Evaluate and optimize prompt performance using structured methods
- Reduce inaccuracies, ambiguity, and repetitive responses
- Utilize prompt frameworks and reusable prompt templates
- Apply prompt engineering to content creation, analysis, automation, and decision support
Who should attend
Target audience
- AI and digital transformation professionals
- Business analysts and consultants
- IT professionals and developers
- Data and innovation specialists
- Content creators and knowledge workers
- Project managers and business leaders
- Anyone seeking to leverage Generative AI tools effectively
- Target Competencies
Methodology
Learning approach
- The course combines interactive presentations, hands-on workshops, practical exercises, AI demonstrations, group discussions, prompt design labs, real-world case studies, and project-based learning to ensure practical application of prompt engineering techniques.
Course content
Five focused days of learning and application
Day 1
Foundations of Large Language Models (LLMs)
- Understanding the fundamentals of Large Language Models and Generative AI technologies
- Exploring the capabilities, limitations, and business applications of LLMs
- Understanding different language model architectures and their use cases
- Reviewing autoregressive, transformer-based, and encoder-decoder models
- Understanding pre-trained, fine-tuned, multilingual, and hybrid AI models
- Identifying opportunities for AI adoption across business functions and industries
Day 2
Introduction to Prompt Engineering
- Understanding the role of prompts in AI interactions and output quality
- Defining prompt engineering concepts and best practices
- Exploring the essential components of effective prompts, including instructions, context, inputs, and output requirements
- Applying common prompt design patterns to improve AI performance
- Understanding persona-based, audience-focused, and structured interaction approaches
- Exploring zero-shot, few-shot, and example-based prompting techniques
- Practical exercises on prompt construction and refinement
Day 3
Designing High-Performance Prompts
- Understanding the characteristics of effective and reliable prompts
- Applying prompt design principles to improve clarity and consistency
- Establishing performance metrics for evaluating prompt effectiveness
- Adjusting prompt parameters and settings to optimize outputs
- Controlling response style, structure, and level of detail
- Reducing ambiguity, repetition, and undesired model behavior
- Practical workshop on prompt optimization and performance testing
Day 4
Advanced Prompt Engineering Techniques
- Developing reusable prompt frameworks and prompt libraries
- Understanding semantic search, embeddings, and knowledge retrieval concepts
- Applying reasoning-oriented prompting techniques to improve problem-solving outcomes
- Utilizing generated knowledge approaches to enhance response quality
- Implementing consistency and validation techniques for complex tasks
- Exploring structured reasoning frameworks and advanced AI interaction strategies
- Practical exercises on advanced prompt design and testing
Day 5
Prompt Engineering Applications and Future Trends
- Applying prompt engineering techniques to business and technical use cases
- Developing prompts for content generation, summarization, and information analysis
- Utilizing AI for coding assistance, documentation, and productivity enhancement
- Understanding ethical considerations, responsible AI use, and governance principles
- Identifying and troubleshooting common prompt design challenges
- Exploring emerging trends and future developments in prompt engineering
- Final project: Designing, testing, and presenting a high-impact prompt solution
- Course recap, lessons learned, and Q&A session
FAQ
Frequently asked questions
What does Master the Art of Prompt Engineering (DIT-010) cover?
This course covers Digital Innovation and Transformation through a structured five-day outline focused on practical application, discussion, and implementation planning.
When is the next available session?
The next scheduled session starts on Schedule on request, with additional classroom dates and mirrored Online / Live options listed in the course schedules section.
Who should attend this course?
AI and digital transformation professionals, Business analysts and consultants, IT professionals and developers
How can I register for a session?
Use any Register button next to the available course dates to open the participant registration page and submit your booking request for the selected session.
Is this course available online as well as classroom-based?
Yes. The course detail page includes both classroom sessions and Online / Live sessions, with online options aligned to the same course dates for easier planning.
Where are classroom sessions delivered?
Classroom venues are confirmed in the schedule panel for each published session.
Still Have Questions?
Contact the academy team for course details, delivery options, and delegate guidance.
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