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Course Outline
Introduction to Generative AI and Prompt Engineering
- Defining generative AI and distinguishing it from conventional automation
- The impact of prompt engineering on the quality of AI-generated output
- A snapshot of the current landscape of text, image, audio, and video generation tools
- Identifying where prompt engineering delivers tangible business value
Foundations of AI Models for Text and Image Generation
- Understanding large language models and diffusion models in accessible terms
- Distinguishing between training data, fine-tuning, and prompting
- Evaluating the capabilities and limitations of pre-trained models
- How model architecture influences prompt formulation
Comparing the Leading AI Assistants
- Microsoft Copilot: Highlights its strengths in Microsoft 365 integration (Word, Excel, Outlook, Teams), enterprise data grounding, while noting limitations in creative range and reasoning depth compared to competitors
- Google Gemini: Recognizing its advantages in native multimodality, Workspace integration, and real-time search grounding, alongside challenges in consistency, regional availability, and complex instruction adherence
- ChatGPT: Leveraging its mature ecosystem, custom GPTs, DALL-E image generation, and voice mode, while acknowledging issues with factual reliability without grounding and stricter limits on premium features
- Claude: Valuing its long-context handling, nuanced reasoning, and analytical clarity, while noting constraints in tool ecosystem breadth and image generation capabilities
- Selecting the optimal tool based on specific tasks, target audiences, or compliance requirements
- A comparative walkthrough applying the same prompt across all four platforms
Principles of Effective Prompt Design
- Establishing clarity, specificity, and context as the core elements of effective prompting
- Structuring instructions, tone, formatting, and constraints
- Identifying and correcting common beginner mistakes
- Iterating from basic prompts to highly optimized ones
Zero-Shot, One-Shot, and Few-Shot Prompting
- Differentiating these approaches and determining their optimal use cases
- Interpreting model behavior to adjust examples effectively
- Training a model on new tasks using a small set of well-selected samples
- Hands-on practice across ChatGPT, Copilot, Gemini, and Claude
Advanced Prompt Engineering Techniques
- Using conditional and context-aware prompts for nuanced results
- Applying style transfer, persona prompting, 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
- Understanding few-shot fine-tuning and its distinction from full model training
- Adapting models to niche tasks through example-driven prompting
- Deciding between prompt engineering and fine-tuning for specific investments
- Assessing output quality and refining through iteration
Hyper-Realistic Text Generation
- Producing text with precise control over tone, voice, and length
- Generating long-form content, summaries, reports, and structured documents
- Maintaining logical coherence across multi-step generation tasks
- Combining prompt patterns to achieve consistent, brand-aligned outcomes
Applying Prompt Engineering to Business Workflows
- Automating routine drafting, research, and information triage
- Exploring applications in customer support and chatbot interactions
- Creating 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
- A comparative analysis of DALL-E, Stable Diffusion, MidJourney, and Leonardo AI
- Crafting prompts to control style, composition, lighting, and subject matter
- Utilizing negative prompts, weighting, and iterative refinement techniques
- Performing image-to-image transformations and editing via prompts
Audio and Speech with AI
- Generating natural-sounding speech from text inputs
- Conceptual understanding of voice cloning and synthesis
- Applications in training materials, accessibility, and marketing campaigns
Video Content Creation with Generative AI
- An overview of current text-to-video tools and their realistic capabilities
- Scripting and storyboarding through sequential prompts
- Integrating AI-generated text, images, audio, and video into cohesive assets
- Editing and refining AI-created video content
Multimodal AI and Integrated Workflows
- How multimodal models integrate 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
- Navigating bias, copyright, attribution, and content moderation
- Privacy and data protection considerations in generative AI usage
- Maintaining disclosure, transparency, and trust with end-users
- Emerging tools, models, and trends to monitor over the next 12 months
Requirements
Intended Audience
Professionals in marketing, communications, and creative fields seeking to enhance content production with AI. Operational and customer-facing teams aiming to streamline repetitive interactions via prompt-driven solutions. Absolute beginners with no prior background in AI or programming who desire a structured, tool-centric introduction to the world of generative AI.
21 Hours
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 3900 € + VAT*
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Testimonials (2)
use of proper and effective prompt
Marses Pacaldo
Course - Generative AI and Prompt Engineering for Corporate Professionals
The interactive style, the exercises
