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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-generated output
- A survey of the current landscape of text, image, audio, and video tools
- Identifying where prompt engineering delivers tangible business value
Foundations of AI Models for Text and Image Generation
- Plain-language explanations of how large language models and diffusion models function
- Distinguishing between training data, fine-tuning, and prompting
- Understanding the capabilities and limitations of pre-trained models
- How model architecture influences prompt writing strategies
Comparing Leading AI Assistants
- Microsoft Copilot: Highlighting its strengths in Microsoft 365 integration across Word, Excel, Outlook, and Teams, as well as enterprise data grounding, while noting limitations in creative range and deep reasoning compared to competitors
- Google Gemini: Focusing on its native multimodality, Workspace integration, and real-time search grounding, while addressing challenges related to consistency, regional availability, and instruction-following in complex tasks
- ChatGPT: Emphasizing its mature ecosystem, custom GPTs, DALL-E image generation, and voice mode, while acknowledging issues with factual reliability without grounding and stricter usage limits on premium features
- Claude: Showcasing its ability to handle long contexts, nuanced reasoning, and lengthy writing with clear analysis, while noting the narrower tool ecosystem and lack of built-in image generation
- Selecting the optimal tool based on specific tasks, target audiences, or compliance requirements
- A comparative walkthrough demonstrating the same prompt across all four assistants
Principles of Effective Prompt Design
- Establishing clarity, specificity, and context as the core pillars of effective prompting
- Organizing instructions, tone, format, and constraints
- Identifying common beginner errors and how to detect them
- Refining weak prompts into high-performing instructions through iteration
Zero-Shot, One-Shot, and Few-Shot Prompting
- Differentiating between these three approaches and determining appropriate use cases
- Interpreting model behavior to adjust examples effectively
- Teaching models new tasks using a small set of carefully selected samples
- Hands-on exercises utilizing ChatGPT, Copilot, Gemini, and Claude
Advanced Prompt Engineering Techniques
- Creating conditional and context-aware prompts for nuanced results
- Employing 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
- Defining few-shot fine-tuning and differentiating it from full model training
- Adapting models to niche tasks through example-driven prompts
- Determining when prompt engineering suffices versus when fine-tuning is a better investment
- Assessing output quality and refining processes iteratively
Hyper-Realistic Text Generation
- Generating text with precise control over tone, voice, and length
- Producing long-form content, summaries, reports, and structured documents
- Maintaining coherence across multi-step generation processes
- Combining prompt patterns for consistent, brand-aligned outcomes
Applying Prompt Engineering to Business Workflows
- Automating routine drafting, research, and information triage
- Briefly exploring customer support and chatbot applications
- Designing 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 that control style, composition, lighting, and subject matter
- Utilizing negative prompts, weighting, and iterative refinement
- Performing image-to-image transformations and editing via prompts
Audio and Speech with AI
- Generating natural-sounding speech from text prompts
- Understanding voice cloning and synthesis at a conceptual level
- Exploring use cases in training content, accessibility, and marketing
Video Content Creation with Generative AI
- Reviewing current text-to-video tools and their realistic capabilities
- Scripting and storyboarding through sequential prompts
- Synthesizing AI-generated text, images, audio, and video into unified assets
- Editing and refining AI-created video output
Multimodal AI and Integrated Workflows
- Understanding how multimodal models integrate text, image, audio, and video reasoning
- Building end-to-end content pipelines without coding
- Analyzing 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 for the next 12 months
Requirements
Target Audience
Marketing, communications, and creative professionals seeking to explore AI-assisted content production. Business operations and customer-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.
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
