Advanced Prompt Applications and Futures

This capstone unit surveys practical examples across multiple generative AI systems (image, audio, and latent models), examines ethical and accessibility considerations, and explores future trajectories for each technology. It prepares students to synthesize prompt engineering techniques into a professional portfolio, career plan, and continuing-education strategy while staying current with advanced methods and community practices.

Learning Objectives

• Analyze multiple generative AI systems (DeepFaceLab, DeepArt Effects, AIVA, WaveNet, ImageNet, VQ-VAE) to produce a comparative evaluation of their real-world use cases, strengths, limitations, and future trajectories.
• Apply prompt engineering strategies to design, test, and optimize prompts across at least three different model types (image, audio, and latent-vector), documenting results and performance trade-offs.
• Evaluate ethical, legal, and accessibility implications of deploying generative models in practical scenarios and recommend concrete mitigation strategies and safeguards.
• Demonstrate professional readiness by creating a prompt-engineering portfolio and a career-development plan that includes advanced techniques, community engagement, and continuing-education pathways.