/ai-101

Explore the fundamentals of generative AI in this introductory course, covering its core principles, applications, and underlying technologies. Delve into various AI modalities, examine real-world uses, and navigate the ethical landscape shaping AI's future

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Generative AI 101

Explore the fundamentals of generative AI in this introductory course, covering its core principles, applications, and underlying technologies. Delve into various AI modalities, examine real-world uses, and navigate the ethical landscape shaping AI's future

Course Overview

  • Introduce the basics of generative AI, including its principles and applications.
  • Explore key technologies behind generative AI, such as Large Language Models and neural networks.
  • Dive into specific AI modalities including text, image, voice, video and vector generation.
  • Highlight real-world applications, open-source tools, and ethical considerations.
  • Equip learners with the knowledge to understand and engage with the latest AI innovations.

Lessons

Lesson 1: Introduction to Generative AI

  • Fundamentals and history
  • Key concepts and applications

Lesson 2: Basics of Machine Learning for Generative AI

  • Machine learning and neural networks overview
  • Discriminative vs. generative models

Lesson 3: Understanding Large Language Models (LLMs)

  • How large language models work
  • Architecture, tokens, and tokenization
  • Parameters, weights, and the training process

Lesson 4: Generative AI Mechanics

  • Generation process, temperature, and prompts
  • Fine-tuning and transfer learning
  • Building advanced prompts and use cases

Lesson 5: Text Generation

  • Understanding text generation models
  • Applications and products
  • Open-source models and how to use them.

Lesson 6: Image Generation

  • Understanding image generation models
  • Applications in art, design, and more
  • Open-source models and how to use them.

Lesson 7: Embedding Generation

  • Role of embeddings in similarity search, recommendation systems
  • Techniques for generating embeddings
  • Open-source models and how to use them.

Lesson 8: Voice Generation and Voice-to-Text

  • Text-to-Speech (TTS) and Speech-to-Text (STT) technologies
  • Use cases in virtual assistants, audiobooks, etc.
  • Open-source models and how to use them.

Lesson 9: Video Generation

  • Techniques for generating and manipulating videos
  • Applications in entertainment and education
  • Open-source models and how to use them.

Lesson 10: Multi-Modal Generative AI

  • Combining modalities for advanced applications
  • examples of multi-modal applications

Lesson 11: Generative AI in Products and Services

  • Real-world applications of generative AI
  • Gen-AI in healthcare and education.

Lesson 12: AI Safety and Ethical Considerations

  • Challenges in AI safety and ethics
  • Strategies for mitigating risks

Lesson 13: Future Directions and Innovations in Generative AI

  • Research trends, challenges, and opportunities
  • Community and collaboration
  • How to stay updated with the latest in generative AI