Generative AI for Everyone

This course provides a comprehensive introduction to the world of Generative AI, offering non-technical participants the foundational knowledge they need to understand how generative models work and their wide-ranging applications. The course covers various forms of generative AI, including text generation, image creation, music synthesis, and more, utilizing models like GPT, DALL-E, and other state-of-the-art AI technologies.

By the end of the course, students will understand how generative AI works, its real-world applications, and the ethical considerations surrounding its use

Course Objectives:

Understand the fundamental principles of generative AI.
Explore different generative AI models and their applications.
Gain hands-on experience with user-friendly tools for text, image, and music generation.
Discuss the ethical implications and limitations of generative AI.
Learn how generative AI is being used in various industries like art, entertainment, and healthcare.

Course content

Module 1: Introduction to Artificial Intelligence and Generative AI

What is Artificial Intelligence?
Understanding the broader field of AI and machine learning.

What is Generative AI?Introduction to generative models and how they differ from traditional AI.
Overview of key concepts: Neural networks, deep learning, and probability.

Types of Generative AI:
Text generation, image creation, video synthesis, and music generation.

Hands-on Lab:
Generate simple text prompts using an AI-based text generator like OpenAI’s GPT.

Module 2: Understanding Text Generators

Text Generation Basics:

How generative models like GPT work for text generation.
Use cases: Creative writing, customer support automation, and conversational AI.

Applications of Text Generation:
GPT-3 and ChatGPT applications in marketing, content creation, and automation.

Hands-on Lab:Experiment with text generation using tools like OpenAI’s GPT or other publicly available platforms.
Create automated responses and explore creative writing prompts.

Module 3: Image Generation with AI

Image Generation Basics

How AI models like DALL-E and Stable Diffusion generate images from text descriptions.
Understanding latent space and how AI learns to generate images.

Applications of Image Generation:
How generative AI is transforming industries like advertising, design, and digital art.

Hands-on Lab:Use DALL-E or similar tools to generate images from text-based inputs.
Explore creativity in art and design using AI-generated artwork.

Module 4: Music and Video Generation with AI

AI-Generated Music:

Overview of models that generate music, such as OpenAI’s Jukedeck.
How AI can be used to compose music and soundtracks.

AI-Generated Video:

Basics of video generation with AI, focusing on tools like Synthesia for creating AI-driven video content.
Applications in video marketing, film, and virtual influencers.

Hands-on Lab:
Use an AI platform to generate basic music tracks or video content based on provided inputs.

Module 5: Ethical Considerations and Challenges in Generative AI

The Ethics of Generative AI:

Understanding biases in AI-generated content.
Intellectual property and originality issues.
Misinformation, deepfakes, and fake news: The dark side of generative AI.

Legal and Societal Implications:
Regulatory concerns and the future of AI governance.

Group Discussion:
Explore real-world examples of ethical challenges in generative AI applications.

Module 6: Industry Use Cases of Generative AI (2 Hours)
Art and Design:
How artists and designers are leveraging generative AI tools for creative work.

Healthcare:
Applications in medical imaging and drug discovery using AI-generated data.

Entertainment and Media:
The use of AI in scriptwriting, video editing, and creating synthetic media.

Marketing and Advertising:
AI-generated content and personalized advertising campaigns.

Case Studies:
Real-world examples of generative AI being used in various industries.

International Student Fees: USD: 350$

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