Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Generative AI and Prompt Engineering
- Understanding generative AI and how it distinguishes itself from traditional automation
- The impact of prompt engineering on the quality of AI outputs
- An overview of the current ecosystem of text, image, audio, and video tools
- Identifying where prompt engineering delivers tangible business value
Foundations of AI Models for Text and Image Generation
- Explaining how large language models and diffusion models function in simple terms
- Differentiating between training data, fine-tuning, and prompting
- Examining the strengths and limitations of pre-trained models
- Understanding how model architecture influences prompt writing strategies
Comparing the Leading AI Assistants
- Microsoft Copilot: Strengths in Microsoft 365 integration (Word, Excel, Outlook, Teams), enterprise data grounding; and limitations in creative range and reasoning depth compared to peers
- Google Gemini: Strengths in native multimodality, Workspace integration, and real-time search grounding; and weaknesses in consistency, regional availability, and complex instruction-following
- ChatGPT: Strengths in ecosystem maturity, custom GPTs, image generation via DALL-E, and voice mode; and weaknesses in factual reliability without grounding and stricter limits on premium features
- Claude: Strengths in long-context handling, nuanced reasoning, longer-form writing, and analytical clarity; and weaknesses in the breadth of its tool ecosystem and image generation capabilities
- Selecting the appropriate tool based on specific tasks, audiences, or compliance requirements
- A comparative walkthrough of the same prompt across all four assistants
Principles of Effective Prompt Design
- Clarity, specificity, and context as the core pillars of effective prompting
- Structuring instructions, tone, format, and constraints effectively
- Identifying common beginner errors and how to recognise them
- The process of iterating from a weak prompt to a high-performing one
Zero-Shot, One-Shot, and Few-Shot Prompting
- Distinguishing between the three approaches and determining when each is most appropriate
- Interpreting model behaviour and adjusting examples accordingly
- Teaching models new tasks using a small number of well-chosen samples
- Practical exercises across ChatGPT, Copilot, Gemini, and Claude
Advanced Prompt Engineering Techniques
- Creating conditional and context-aware prompts for nuanced outputs
- Applying style transfer, persona prompting, and creative direction
- Utilising chain-of-thought and step-by-step reasoning prompts
- Mitigating hallucinations, ambiguity, and bias in AI responses
Few-Shot Fine-Tuning Without Code
- Defining few-shot fine-tuning and differentiating it from full model training
- Adapting models to niche tasks using example-driven prompts
- Deciding when to prompt-engineer versus when fine-tuning offers better value
- Evaluating output quality and refining iteratively
Hyper-Realistic Text Generation
- Generating text with controlled tone, voice, and length
- Producing long-form content, summaries, reports, and structured documents
- Maintaining coherence across multi-step generation processes
- Combining prompt patterns to achieve repeatable, brand-aligned results
Applying Prompt Engineering to Business Workflows
- Automating routine drafting, research, and information triage
- An examination of customer support and chatbot use cases
- Designing reusable prompt templates for teams without retraining
- Implementing quality control, escalation logic, and human-in-the-loop checkpoints
Image Generation and Manipulation
- A comparison of DALL-E, Stable Diffusion, MidJourney, and Leonardo AI
- Crafting prompts to control style, composition, lighting, and subject matter
- Utilising negative prompts, weighting, and iterative refinement
- Performing image-to-image transformation and editing through prompts
Audio and Speech with AI
- Generating natural-sounding speech from text prompts
- Conceptual overview of voice cloning and synthesis
- Exploring use cases in training content, accessibility, and marketing
Video Content Creation with Generative AI
- An overview of current text-to-video tools and their realistic capabilities
- Scripting and storyboarding through sequential prompting
- Integrating AI-generated text, images, audio, and video into unified assets
- Editing and refining AI-created video output
Multimodal AI and Integrated Workflows
- How multimodal models unify reasoning across text, image, audio, and video
- Building end-to-end content pipelines without coding
- Real-world case studies from marketing, design, training, and advertising
Ethics, Responsible Use, and Future Trends
- Addressing bias, copyright, attribution, and content moderation
- Privacy and data protection considerations when using generative platforms
- Ensuring disclosure, transparency, and trust with end customers
- Emerging tools, models, and trends to monitor over the next 12 months
Requirements
Target Audience
This course is ideal for marketing, communications, and creative professionals exploring AI-assisted content production. It is also well-suited for business operations and customer-facing teams seeking to automate repetitive interactions using prompt-driven tools. Additionally, it provides a structured, tool-focused entry point for beginners with no prior AI or programming experience.
21 Hours
Testimonials (2)
use of proper and effective prompt
Marses Pacaldo
Course - Generative AI and Prompt Engineering for Corporate Professionals
The interactive style, the exercises
