Course Outline
Day 1
Introduction to Generative AI and Prompt Engineering
- Understanding generative AI and how it contrasts with traditional automation
- The critical role of prompt engineering in influencing the quality of AI outputs
- A survey of the current landscape of text, image, audio, and video AI tools
- Identifying where prompt engineering delivers the most business value
Foundations of AI Models for Text and Image Generation
- A plain-language explanation of how large language models and diffusion models operate
- Distinguishing between training data, fine-tuning, and prompting
- Recognizing the strengths and limitations of pre-trained models
- Understanding why model architecture dictates prompt writing strategies
Comparing the Leading AI Assistants
- Microsoft Copilot: Highlights include deep integration with Microsoft 365 (Word, Excel, Outlook, Teams), enterprise data grounding, and areas for improvement such as creative range and reasoning depth compared to competitors.
- Google Gemini: Highlights include native multimodality, Workspace integration, and real-time search grounding, with noted challenges in consistency, regional availability, and executing complex instructions.
- ChatGPT: Highlights include a mature ecosystem, custom GPT capabilities, DALL-E image generation, and voice mode, alongside potential drawbacks like factual reliability issues without grounding and stricter limits on premium features.
- Claude: Highlights include superior long-context handling, nuanced reasoning, long-form writing, and analytical clarity, with limitations in tool ecosystem breadth and image generation capabilities.
- Strategies for selecting the optimal tool based on specific tasks, audiences, or compliance requirements
- A comparative demonstration running the same prompt across all four platforms
Principles of Effective Prompt Design
- Establishing clarity, specificity, and context as the core pillars of strong prompts
- Structuring instructions, tone, format, and constraints effectively
- Identifying common beginner mistakes and learning how to spot them
- The process of iterating from an initial weak prompt to a high-performing one
Day 2
Zero-Shot, One-Shot, and Few-Shot Prompting
- Differentiating between the three approaches and knowing when to apply each
- Observing model behavior and adjusting example inputs accordingly
- Teaching a model new tasks using only a carefully selected few samples
- Hands-on exercises across ChatGPT, Copilot, Gemini, and Claude
Advanced Prompt Engineering Techniques
- Utilizing conditional and context-aware prompts for nuanced results
- Employing style transfer, persona adoption, and creative direction
- Implementing 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 distinguishing it from full model training
- Adapting models for niche tasks using example-driven prompting
- Determining when prompt engineering is sufficient versus when fine-tuning offers better ROI
- Evaluating output quality and refining through iterative cycles
Hyper-Realistic Text Generation
- Creating text with precise control over tone, voice, and length
- Producing long-form content, summaries, reports, and structured documents
- Ensuring coherence during multi-step generation processes
- Combining prompt patterns to achieve repeatable, brand-consistent results
Applying Prompt Engineering to Business Workflows
- Automating routine drafting, research tasks, and information triage
- Exploring use cases for customer support and chatbots
- Designing reusable prompt templates for teams without the need for retraining
- Implementing quality control measures, escalation logic, and human-in-the-loop checkpoints
Day 3
Image Generation and Manipulation
- Comparing DALL-E, Stable Diffusion, MidJourney, and Leonardo AI
- Crafting prompts that control style, composition, lighting, and subject matter
- Using 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 directly from text prompts
- Understanding voice cloning and synthesis at a conceptual level
- Exploring applications in training content, accessibility, and marketing
Video Content Creation with Generative AI
- Overview of current text-to-video tools and their realistic capabilities
- Developing scripts and storyboards through prompt sequences
- Integrating AI-generated text, images, audio, and video into cohesive assets
- Editing and refining video output created by AI
Multimodal AI and Integrated Workflows
- How multimodal models unify reasoning across text, image, audio, and video
- Constructing end-to-end content pipelines without coding
- Real-world case studies from marketing, design, training, and advertising sectors
Ethics, Responsible Use, and What Comes Next
- Addressing bias, copyright, attribution, and content moderation issues
- Considering privacy and data protection when utilizing generative platforms
- Maintaining disclosure, transparency, and trust with end customers
- Emerging tools, models, and trends to monitor over the coming year
- Summary and next steps for continued learning
Requirements
Intended Audience
Marketing, communications, and creative professionals seeking to leverage AI for content production. Business operations and customer-facing teams aiming to automate repetitive tasks using prompt-based tools. Complete beginners with no prior exposure to AI or programming who desire a structured, tool-centric introduction to 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)
