Generative AI

Generative AI: Foundations and Applications

Generative AI is revolutionizing the way we think about creativity, design, and data generation. By leveraging deep learning and neural networks, generative AI models can produce new content, from realistic images and text to synthetic data and music. This course demystifies the technology behind generative AI and explores its practical applications across various industries.

Program Objectives

  • Understand the foundational concepts of generative AI, including key models like GANs, VAEs, and Transformers.
  • Explore the applications of generative AI in creating art, music, text, and synthetic data.
  • Learn the ethical considerations and implications of using generative AI technologies.
  • Gain hands-on experience with generative AI tools and frameworks.

Target Audience This course is ideal for AI enthusiasts, creative professionals, developers, and anyone interested in understanding and applying generative AI technologies in their field.


  • Master the concepts and techniques behind generative AI.
  • Learn to apply generative AI in creative and innovative ways.
  • Understand the ethical dimensions of generative content creation.
  • Gain practical skills in using generative AI models for various applications.

Course Outline for Generative AI: Foundations and Applications

1. Introduction to Generative AI

  • Overview of the transformative impact of Generative AI on creativity, design, and data generation.

2. Foundational Concepts and Technologies
  • Basics of deep learning and neural networks as pivotal to generative AI.
  • Introduction to core generative technologies: GANs, VAEs, Transformers.

3. Generative Adversarial Networks (GANs)
  • Deep dive into GAN architecture and functioning.
  • Hands-on project: Building a GAN to generate images.

4. Variational Autoencoders (VAEs)
  • Examination of VAEs, their structure, and their role in data generation.
  • Practical activity: Developing a VAE to generate new data.

5. Natural Language Processing (NLP) and Generative AI
  • The significance of NLP in generative AI, from RNNs and LSTMs to advanced models.
  • Introduction to NLP applications in text generation and processing.

6. Large Language Models (LLMs) and Big Tech Innovations
  • In-depth exploration of LLMs like BERT, GPT (OpenAI), and T5, highlighting contributions from Google, OpenAI, and other tech giants.
  • Hands-on: Experimenting with GPT and BERT for text generation, showcasing the advancements made by these organizations.

7. Stable Diffusion and the Latest Models from Big Tech
  • Introduction to Stable Diffusion and its significance, including contributions from companies like OpenAI (DALLĀ·E) and others in the space.
  • Creative projects with Stable Diffusion, understanding its industrial and artistic applications.

8. The Role of Big Tech in Generative AI Applications
  • Examination of how major tech companies are applying generative AI in various domains.
  • Discussion on the ecosystem fostered by big tech, including platforms, tools, and APIs for developers and creatives.

9. Ethical Considerations in Generative AI
  • Ethical implications of generative AI, with a focus on the responsibilities of big tech companies in shaping ethical usage.
  • Group discussion: Debating real-world scenarios influenced by generative AI technologies.

10. Project: Implementing Generative AI
  • Application of course concepts in a comprehensive project, possibly utilizing platforms and tools provided by big tech companies.

11. Conclusion and Next Steps in Generative AI
  • Guidance on further resources, communities, and development paths for continued learning in the rapidly evolving field of generative AI.

This course outline aims to provide a comprehensive overview of Generative AI, emphasizing the significant role of big tech companies in advancing the field. Participants will gain not only theoretical knowledge and practical skills but also insights into the industry's direction, driven by the innovations and ethical considerations of leading tech players.