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Preamble to Fundamentals of Generative AI Course

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A preamble is an introductory statement or introduction to a document or speech, setting the tone and context for what follows. It often outlines the purpose, objectives, or philosophical principles behind the document.

For example, in legal documents like constitutions, the preamble provides the foundational reasons and goals of the legislation. A well-known example is the preamble of the United States Constitution, which begins with “We the People” and expresses the intent to establish justice and promote general welfare.

In other contexts, such as essays or reports, a preamble can summarize the main ideas or arguments that will be detailed later.

🤖 Source OutLine for Findamentals of AI Course 🤖

Fundamentals of Generative AI


Module 1: Introduction to Generative AI

  • Lesson 1.1: What is Generative AI?
  • Definition and key concepts
  • Difference between generative and discriminative models
  • Lesson 1.2: Applications of Generative AI
  • Content creation (text, images, music)
  • Data augmentation
  • Simulation and modeling

Module 2: Core Concepts and Techniques

  • Lesson 2.1: Machine Learning Basics
  • Overview of machine learning types (supervised, unsupervised, reinforcement)
  • Introduction to neural networks
  • Lesson 2.2: Generative Models Explained
  • Variational Autoencoders (VAEs)
  • Generative Adversarial Networks (GANs)
  • Diffusion models

Module 3: Implementing Generative AI

  • Lesson 3.1: Setting Up Your Environment
  • Required software and tools (Python, TensorFlow, PyTorch)
  • Data handling and preprocessing
  • Lesson 3.2: Building a Simple Generative Model
  • Step-by-step example: Creating a GAN
  • Training and evaluation of the model
  • Common pitfalls and troubleshooting

Module 4: Ethical Considerations and Future Trends

  • Lesson 4.1: Ethical Implications of Generative AI
  • Misuse and deepfakes
  • Bias in training data
  • Lesson 4.2: The Future of Generative AI
  • Emerging trends in technology and applications
  • Discussion on regulation and ethical frameworks

Course Completion

  • Assessment:
  • Quiz covering key concepts from all modules
  • Further Learning Resources:
  • Recommended reading materials
  • Online courses and tutorials

By the end of this course, participants should have a solid understanding of what Generative AI is, how it works, and the implications of its use in various fields. They will also have hands-on experience with a simple generative model.