Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Generative AI and Prompt Engineering
- Understanding generative AI and how it diverges from conventional automation
- The impact of prompt engineering on the quality of AI outputs
- A survey of the current landscape of text, image, audio, and video generation tools
- Identifying where prompt engineering creates tangible business value
Foundations of AI Models for Text and Image Generation
- Simplified explanations of how large language models and diffusion models function
- Distinguishing between training data, fine-tuning, and prompting
- Assessing the capabilities and limitations of pre-trained models
- Understanding how model architecture influences prompt construction
Comparing Leading AI Assistants
- Microsoft Copilot: highlights include deep integration with Microsoft 365, Word, Excel, Outlook, and Teams, alongside enterprise data grounding; limitations involve creative range and depth of reasoning relative to competitors
- Google Gemini: strengths lie in native multimodality, Workspace integration, and real-time search grounding; challenges include consistency issues, regional availability, and handling complex instructions
- ChatGPT: advantages include a mature ecosystem, custom GPTs, DALL-E image generation, and voice mode; drawbacks include factual reliability without external grounding and strict usage limits on premium features
- Claude: excels in long-context processing, nuanced reasoning, extensive writing, and clear analysis; limitations concern the breadth of its tool ecosystem and image generation capabilities
- Selecting the optimal tool based on specific tasks, target audiences, or compliance requirements
- A comparative walkthrough applying identical prompts across all four assistants
Principles of Effective Prompt Design
- The three core elements of a robust prompt: clarity, specificity, and context
- Organizing instructions, tone, format, and constraints effectively
- Identifying and avoiding common errors made by beginners
- Refining weak prompts into high-performance ones through iteration
Zero-Shot, One-Shot, and Few-Shot Prompting
- Distinguishing between these three approaches and determining appropriate use cases
- Interpreting model behavior to adjust examples effectively
- Guiding a model toward new tasks using a small number of well-selected samples
- Hands-on exercises utilizing ChatGPT, Copilot, Gemini, and Claude
Advanced Prompt Engineering Techniques
- Crafting conditional and context-aware prompts for nuanced results
- Employing style transfer, persona prompting, and creative direction
- Utilizing chain-of-thought and step-by-step reasoning prompts
- Mitigating hallucinations, ambiguity, and bias in generated 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 prompting
- Determining when prompt engineering is sufficient versus when fine-tuning is a better investment
- Assessing output quality and refining results through iterative processes
Hyper-Realistic Text Generation
- Generating text with precise control over tone, voice, and length
- Creating long-form content, summaries, reports, and structured documents
- Maintaining coherence throughout multi-step generation processes
- Combining prompt patterns to achieve consistent, brand-aligned results
Applying Prompt Engineering to Business Workflows
- Automating routine drafting, research, and information triage tasks
- An examination of 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
- A comparison of DALL-E, Stable Diffusion, MidJourney, and Leonardo AI
- Writing prompts that dictate style, composition, lighting, and subject matter
- Utilizing 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 from text-based prompts
- An overview of voice cloning and synthesis concepts
- Exploring applications in training materials, accessibility, and marketing
Video Content Creation with Generative AI
- An overview of current text-to-video tools and their realistic capabilities
- Developing scripts and storyboards through sequential prompting
- Synthesizing AI-generated text, images, audio, and video into unified assets
- Editing and refining AI-produced video output
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 Future Trends
- Addressing bias, copyright, attribution, and content moderation issues
- Considering privacy and data protection when utilizing generative platforms
- Maintaining disclosure, transparency, and trust with end users
- Anticipating emerging tools, models, and trends for the next 12 months
Requirements
Intended Audience
This course is designed for marketing, communications, and creative professionals seeking to explore AI-assisted content production. It also suits business operations and customer-facing teams aiming to streamline repetitive interactions using prompt-driven solutions. Furthermore, it serves as a structured, tool-centric entry point for beginners with no prior experience in AI or programming who wish to understand 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
