Course Outline
Day 1
Introduction to Generative AI and Prompt Engineering
- Understanding generative AI and its distinction from traditional automation
- The critical role of prompt engineering in determining AI output quality
- Overview of the current ecosystem for text, image, audio, and video tools
- Identifying where prompt engineering delivers business value
Foundations of AI Models for Text and Image Generation
- A plain-language explanation of how large language models and diffusion models function
- Distinguishing between training data, fine-tuning, and prompting
- Understanding the strengths and limitations of pre-trained models
- How model architecture influences prompt creation strategies
Comparing the Leading AI Assistants
- Microsoft Copilot: Strengths in Microsoft 365 integration (Word, Excel, Outlook, Teams), enterprise data grounding; weaknesses in creative range and reasoning depth compared to competitors
- Google Gemini: Strengths in native multimodality, Workspace integration, real-time search grounding; weaknesses in inconsistency, regional availability, and handling complex instructions
- ChatGPT: Strengths in ecosystem maturity, custom GPTs, DALL-E image generation, voice mode; weaknesses in factual reliability without grounding and stricter usage limits on premium features
- Claude: Strengths in long-context handling, nuanced reasoning, long-form writing, and clear analysis; weaknesses in the breadth of its tool ecosystem and image generation capabilities
- Strategies for selecting the appropriate tool based on task, audience, or compliance requirements
- A side-by-side demonstration of the same prompt across all four assistants
Principles of Effective Prompt Design
- Clarity, specificity, and context as the three pillars of an effective prompt
- Structuring instructions, tone, format, and constraints
- Common beginner mistakes and how to identify them
- Iterating from a weak prompt to a high-performing one
Day 2
Zero-Shot, One-Shot, and Few-Shot Prompting
- Differentiating between the three approaches and determining when to use each
- Reading model behavior and adjusting examples accordingly
- Teaching a model a new task using carefully selected samples
- Practical exercises across ChatGPT, Copilot, Gemini, and Claude
Advanced Prompt Engineering Techniques
- Conditional and context-aware prompts for nuanced outputs
- Style transfer, persona prompting, and creative direction
- Chain-of-thought and step-by-step reasoning prompts
- Mitigating hallucinations, ambiguity, and bias in responses
Few-Shot Fine-Tuning Without Code
- Understanding few-shot fine-tuning and its distinction from full model training
- Adapting a model to niche tasks using example-driven prompts
- Determining when to use prompt engineering versus fine-tuning
- 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 for repeatable, brand-aligned results
Applying Prompt Engineering to Business Workflows
- Automating routine drafting, research, and information triage
- An overview of customer support and chatbot use cases
- Designing reusable prompt templates for teams without retraining
- Quality control, escalation logic, and human-in-the-loop checkpoints
Day 3
Image Generation and Manipulation
- Comparing DALL-E, Stable Diffusion, MidJourney, and Leonardo AI
- Writing prompts to control style, composition, lighting, and subject
- Using negative prompts, weighting, and iterative refinement
- Image-to-image transformation and editing through prompts
Audio and Speech with AI
- Generating natural-sounding speech from text prompts
- Concepts of voice cloning and synthesis
- Use cases in training content, accessibility, and marketing
Video Content Creation with Generative AI
- Overview of current text-to-video tools and their realistic capabilities
- Scripting and storyboarding through prompt sequences
- Combining AI-generated text, images, audio, and video into a single asset
- Editing and refining AI-created video output
Multimodal AI and Integrated Workflows
- How multimodal models unify text, image, audio, and video reasoning
- Building end-to-end content pipelines without writing code
- Real-world case studies from marketing, design, training, and advertising
Ethics, Responsible Use, and What Comes Next
- Bias, copyright, attribution, and content moderation
- Privacy and data protection considerations when using generative platforms
- Disclosure, transparency, and trust with end customers
- Emerging tools, models, and trends to watch over the next 12 months
- Summary and Next Steps
Requirements
Targeted Audience
Marketing, communications, and creative professionals interested in AI-assisted content production. Business operations and customer-facing teams seeking to automate repetitive interactions using prompt-driven tools. Beginners with no prior AI or programming experience who desire a structured, tool-focused entry into generative AI.
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
