Overview of Image Generation using Generative AI: Introduction to AI-powered image generation and its applications in design, marketing, and content creation. Overview of key models such as DALL·E, Stable Diffusion, and MidJourney, including their capabilities and differences. Understanding prompt engineering for image generation, including style, composition, and fine-tuning techniques. Exploring ethical considerations, including biases in generated images and copyright concerns. Hands-on experimentation with AI tools to create images based on text prompts and modify existing visuals. Best practices for integrating AI generated images into real-world applications.

Lab: Students will generate images using a text-to-image model, experimenting with different prompts and styles to create unique visuals for a specific theme or project.

Overview of Automated Code Generation using Generative AI: Introduction to AI-powered code generation and its applications in software development, automation, and debugging. Overview of tools like GitHub Copilot, OpenAI Codex, and other AI-assisted coding platforms. Understanding best practices for writing effective prompts to generate functional and optimized code. Exploring code completion, refactoring, and debugging capabilities with Generative AI. Discussion on limitations, ethical considerations, and security risks in AI-generated code. Best practices for integrating AI-generated code into development workflows.

Lab: Students will use an AI coding assistant to generate a simple script or function, modify it for optimization, and test it to ensure correctness.

Overview of Music Personalization for Marketing and Events using Generative AI: Introduction to AI-generated music and its applications in branding, marketing, and personalized event experiences. Overview of AI music generation tools such as AIVA,
Amper Music, and OpenAI’s Jukebox. Understanding how AI can tailor music to match brand identity, audience preferences, and event themes. Exploring prompt-based music creation and customization techniques for dynamic soundscapes. Discussion on ethical considerations, licensing, and copyright implications in AI-generated music. Best practices for integrating AI-composed music into marketing campaigns and event planning.

Lab: Students will use an AI music generation tool to create a short personalized track for a specific brand or event theme, adjusting parameters to fit the desired mood and style.

Overview of Developing Your Own Marketing Campaign using Generative AI: Introduction to AI-powered marketing and its role in campaign creation, audience targeting, and content personalization. Overview of Generative AI tools for ad copywriting, social media content, email marketing, and visual asset creation. Understanding AI-driven customer segmentation and sentiment analysis to refine
messaging. Exploring AI-generated A/B testing strategies to optimize marketing performance. Discussion on ethical considerations, brand consistency, and the balance between AI automation and human creativity. Best practices for integrating AI-generated content into a cohesive marketing strategy.

Lab: Students will use Generative AI to create a mini-marketing campaign, including AI-generated ad copy, social media posts, and a promotional image tailored to a specific audience segment.

Overview of Automated Document Summarization using Generative AI: Introduction to AI-driven document summarization and its applications in research, business intelligence, and content curation. Overview of extractive vs. abstractive summarization
techniques and how Generative AI improves text compression. Hands-on exploration of AI tools like GPT-based models for summarizing long-form content such as reports, articles, and transcripts. Understanding prompt engineering for tailoring summary length, style, and key point extraction. Discussion on challenges like maintaining context, avoiding bias, and ensuring factual accuracy in AI-generated summaries. Best practices for integrating automated summarization into workflows for efficiency and decision-making.

Lab: Students will use a Generative AI tool to summarize a lengthy document, comparing different summarization styles and refining prompts to optimize clarity and conciseness.