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Duration 21 hours
Course Outline
Introduction to Generative AI and Prompt Engineering
- Understanding generative AI and its distinction from traditional automation
- The impact of prompt engineering on the quality of AI outputs
- An overview of the current landscape of text, image, audio, and video tools
- Identifying the business value added by prompt engineering
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
- The strengths and limitations of pre-trained models
- How model architecture influences prompt design
Comparing the Leading AI Assistants
- Microsoft Copilot: Strengths in Microsoft 365 integration (Word, Excel, Outlook, Teams) and enterprise data grounding, versus weaknesses in creative range and reasoning depth compared to competitors
- Google Gemini: Strengths in native multimodality, Workspace integration, and real-time search grounding, versus weaknesses in consistency, regional availability, and complex instruction-following
- ChatGPT: Strengths in ecosystem maturity, custom GPTs, DALL-E image generation, and voice mode, versus weaknesses in factual reliability without grounding and strict premium feature limits
- Claude: Strengths in long-context handling, nuanced reasoning, long-form writing, and clear analysis, versus weaknesses in tool ecosystem breadth and image generation
- Selecting the appropriate tool based on task, audience, or compliance requirements
- A comparative walkthrough of the same prompt across all four assistants
Principles of Effective Prompt Design
- Clarity, specificity, and context: the three pillars of effective prompting
- Structuring instructions, tone, format, and constraints
- Identifying common beginner mistakes
- Iterating from basic prompts to high-performing ones
Zero-Shot, One-Shot, and Few-Shot Prompting
- Differences between these approaches and their appropriate use cases
- Interpreting model behavior and adjusting examples accordingly
- Training a model on new tasks using a small number of well-selected samples
- Practical exercises across ChatGPT, Copilot, Gemini, and Claude
Advanced Prompt Engineering Techniques
- Conditional and context-aware prompts for nuanced results
- Style transfer, persona prompting, and creative direction
- 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 to niche tasks using example-driven prompts
- Determining when prompt engineering is sufficient versus when fine-tuning is a better investment
- 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 in multi-step generation processes
- Combining prompt patterns for consistent, brand-aligned results
Applying Prompt Engineering to Business Workflows
- Automating routine drafting, research, and information triage
- An introduction to customer support and chatbot applications
- Creating reusable prompt templates for teams without requiring retraining
- Implementing quality control, escalation logic, and human-in-the-loop checkpoints
Image Generation and Manipulation
- Comparing DALL-E, Stable Diffusion, MidJourney, and Leonardo AI
- Writing prompts to control style, composition, lighting, and subject matter
- Utilizing negative prompts, weighting, and iterative refinement
- Performing image-to-image transformation and editing via prompts
Audio and Speech with AI
- Generating natural-sounding speech from text prompts
- Conceptual overview of voice cloning and synthesis
- Applications 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 using prompt sequences
- Integrating AI-generated text, images, audio, and video into cohesive 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 What Comes Next
- Addressing bias, copyright, attribution, and content moderation
- Privacy and data protection considerations for generative platforms
- Ensuring disclosure, transparency, and trust with end customers
- Emerging tools, models, and trends to monitor in the coming 12 months
Requirements
Target Audience
Marketing, communications, and creative professionals seeking AI-assisted content production capabilities. Business operations and client-facing teams aiming to streamline repetitive interactions using prompt-driven tools. Beginners with no prior experience in AI or programming who desire a structured, tool-centric introduction to generative AI.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
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Testimonials (2)
Comprehensiveness about the backround; how to do a prompt.
Olaf Kannt - Helios Klinikum Krefeld
Course - Generative AI and Prompt Engineering in Healthcare
use of proper and effective prompt
