Introduction to Generative AI

This course provides a comprehensive introduction to Generative AI, including models such as GANs, Variational Autoencoders, Autoregressive Models, and their applications, evaluation, ethics, and challenges.

Introduction to Generative AI

  • 📚 What is Generative AI?
  • 📈 The role of Generative AI in machine learning
  • 💻 Key applications of Generative AI
Coursera: Introduction to Artificial Intelligence (Stanford University) | Book: Generative Deep Learning by David Foster

Generative Models: GANs

  • 🔄 Understanding the GAN architecture
  • 📊 Training GANs and common challenges
  • 🤖 Applications of GANs
Deep Learning Specialization (Coursera) | GANs in Action by Jakub Langr and Vladimir Bok

Generative Models: Variational Autoencoders

  • 🔍 The concept of autoencoders and VAEs
  • 📉 Understanding probabilistic generative models
  • 🔮 Applications of VAEs
Coursera: Probabilistic Graphical Models | Udacity: Deep Learning by Google

Generative Models: Autoregressive Models

  • 👥 Understanding autoregressive models
  • 📝 Training autoregressive models
  • 🛠️ Applications and limitations of autoregressive models
Fast.ai: Practical Deep Learning for Coders | Book: Deep Learning by Yoshua Bengio, Ian Goodfellow, and Aaron Courville

Applications of Generative AI

  • 🏙️ Image generation and manipulation
  • 📓 Text generation and synthesis
  • 🎨 Creative applications of Generative AI
Deep Learning Specialization on Coursera | Book: Deep Learning for Computer Vision by Rajalingappaa Shanmugamani

Evaluation and Metrics in Generative AI

  • 📏 Common metrics for evaluating Generative AI models
  • 🔍 Challenges in evaluating generative models
  • 📊 Practical techniques for model evaluation
Udemy: Deep Learning and Computer Vision | Book: Deep Learning for NLP and Speech Recognition by Sudipan Dey and Siddhartha Bhattacharyya

Ethics and Challenges in Generative AI

  • 🛡️ Ethical implications of Generative AI
  • 🤔 Challenges in deploying Generative AI models
  • 🔐 Mitigating ethical and technical challenges
Online course: AI Ethics (Stanford University) | Book: Ethical AI by Bill Hibbard
What's next?
© 2023 SqillPlan, Inc