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Course Outline
Introduction to Generative AI and Prompt Engineering
- Understanding generative AI and how it distinguishes itself from traditional automation
- The critical role of prompt engineering in determining the quality of AI outputs
- A survey of the current landscape of tools for text, image, audio, and video generation
- Identifying where prompt engineering delivers tangible business value
Foundations of AI Models for Text and Image Generation
- Explaining the mechanics of large language models and diffusion models in accessible terms
- Differentiating between training data, fine-tuning, and prompting
- Understanding the capabilities and limitations of pre-trained models
- How model architecture influences effective prompt writing
Comparing Leading AI Assistants
- Microsoft Copilot: leveraging strengths in Microsoft 365 integration (Word, Excel, Outlook, Teams), enterprise data grounding, while noting limitations in creative range and reasoning depth
- Google Gemini: utilizing native multimodality, Workspace integration, and real-time search grounding, while addressing challenges in consistency, regional availability, and complex instruction-following
- ChatGPT: benefiting from a mature ecosystem, custom GPTs, DALL-E image generation, and voice mode, while considering constraints on factual reliability without grounding and premium feature limits
- Claude: excelling in long-context handling, nuanced reasoning, and long-form analysis, while acknowledging limitations in tool ecosystem breadth and image generation
- Selecting the most appropriate tool based on specific tasks, target audiences, or compliance requirements
- A comparative walkthrough testing the same prompt across all four assistants
Principles of Effective Prompt Design
- Establishing clarity, specificity, and context as the core pillars of successful prompting
- Structuring instructions, tone, format, and constraints effectively
- Identifying common beginner errors and strategies to avoid them
- Techniques for iterating from a basic prompt to a high-performing one
Zero-Shot, One-Shot, and Few-Shot Prompting
- Distinguishing between zero-shot, one-shot, and few-shot approaches and determining when to use each
- Interpreting model behaviour and adjusting examples accordingly
- Teaching a model new tasks using a small number of well-selected samples
- Practical exercises across ChatGPT, Copilot, Gemini, and Claude
Advanced Prompt Engineering Techniques
- Using conditional and context-aware prompts to achieve nuanced results
- Applying style transfer, persona prompting, and creative direction
- Leveraging chain-of-thought and step-by-step reasoning in prompts
- Strategies to minimise hallucinations, ambiguity, and bias in AI responses
Few-Shot Fine-Tuning Without Code
- Understanding few-shot fine-tuning and how it contrasts with full model training
- Adapting models to niche tasks through example-driven prompting
- Determining when prompt engineering is sufficient versus when fine-tuning offers better value
- Evaluating output quality and refining results iteratively
Hyper-Realistic Text Generation
- Generating text with precise control over tone, voice, and length
- Creating long-form content, summaries, reports, and structured documents
- Maintaining coherence across multiple generation steps
- Combining prompt patterns to achieve repeatable, brand-aligned results
Applying Prompt Engineering to Business Workflows
- Automating routine drafting, research, and information triage
- Exploring customer support and chatbot use cases
- Designing reusable prompt templates for teams without the need for retraining
- Implementing quality control, escalation logic, and human-in-the-loop checkpoints
Image Generation and Manipulation
- Comparing features and outputs of DALL-E, Stable Diffusion, MidJourney, and Leonardo AI
- Crafting prompts that control style, composition, lighting, and subjects
- Utilising negative prompts, weighting, and iterative refinement techniques
- Performing image-to-image transformations and edits via prompts
Audio and Speech with AI
- Generating natural-sounding speech from text inputs
- Understanding voice cloning and synthesis concepts
- Exploring applications in training content, accessibility, and marketing
Video Content Creation with Generative AI
- Reviewing current text-to-video tools and their realistic capabilities
- Developing scripts and storyboards using prompt sequences
- Synthesising AI-generated text, images, audio, and video into cohesive assets
- Editing and refining AI-produced video content
Multimodal AI and Integrated Workflows
- Understanding how multimodal models unify reasoning across text, image, audio, and video
- Building end-to-end content pipelines without coding
- Examining real-world case studies from marketing, design, training, and advertising
Ethics, Responsible Use, and Future Trends
- Addressing bias, copyright, attribution, and content moderation
- Considering privacy and data protection when using generative platforms
- Maintaining disclosure, transparency, and trust with end customers
- Monitoring emerging tools, models, and trends over the next 12 months
Requirements
Intended Audience
Marketing, communications, and creative professionals seeking to adopt AI-assisted content creation. Business operations and customer-facing teams aiming to automate routine interactions using prompt-driven solutions. Complete beginners with no prior experience in AI or programming who are looking for a structured, tool-centric entry point into the world of generative AI.
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
