Unlocking Generative AI with Smart Prompting
About This Course
This course equips learners with a strong foundation in generative AI, focusing on its applications within customer service and hospitality management. Participants will gain critical insights into how generative and discriminative models function, and how to effectively apply generative AI for content summarisation, inference, and service enhancement. With a practical emphasis, learners will develop hands-on skills in prompt engineering—analyzing how prompt variations affect AI outputs and fine-tuning responses to align with service excellence goals.
The course also addresses the ethical dimensions of AI use in customer engagement, training participants to identify risks and evaluate biases in AI-generated interactions. This ensures professionals not only optimize AI tools for operational efficiency but also uphold integrity and inclusivity in customer communication.
Generative AI is revolutionizing customer service and hospitality, offering smarter, faster, and more personalized engagement strategies. Mastering prompt engineering and ethical AI use is increasingly valuable across hotels, travel agencies, restaurants, and service-based platforms. This course enhances employability and supports career progression by equipping learners with skills that are in high demand as the industry embraces AI transformation.
This course is designed for intermediate learners with a basic understanding of customer service or hospitality operations and a curiosity about applying AI solutions in their work.
What You'll Learn
LO1: Demonstrate generative AI concepts and applications relevant to customer service and hospitality management.
LO2: Apply prompt engineering techniques and analyse output variations to improve generative AI performance in service settings.
LO3: Identify ethical risks and analyse bias in AI-generated content used in customer engagement.
Course Outline
LU1: Generative AI Fundamentals
T1: Underlying principles, core concepts and theories governing generative AI
T2: Difference between generative and discriminative models
T3: Demonstrate the use of generation AI in diverse applications (e.g., summarisation, inference, reasoning, transformation of content, augmentation of content)
LU2: Prompt Engineering
T1: Importance of data quality, preprocessing, model pipeline and model training (e.g., impact of data bias from training data)
T2: Impact of prompt engineering on the model outputs of generative AI
T3: Apply understanding of generative AI principles to use cases
T4: Analyse generative AI models' performance metrics and evaluate the influence of prompt variations
LU3: Ethical Considerations
T1: Generative AI model workings, including training data, algorithms, and outputs
T2: Identify the ethical implications and societal impact of AI-generated content
T3: Analyse limitations and potential biases in AI-generated content
Entry Requirements
• Minimum 1 year of work experience in any sector
• WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
• Proficient in using computers and smartphone