10

Lessons

10 days

Duration

English

Language

Course features:

PRE-REQUISITES:

Lab setup:

Learning Path

  • What is Generative AI?
  • Why Generative AI?
  • Generative AI Principles
  • Types of Generative Models
  • Machine Learning Algorithms with Generative AI
  • Applications of Generative AI
  • Generative AI: Advantages and Disadvantages
  • Ethical Considerations
  • Google Colab Introduction
  • Summary and Conclusion
  • Introduction to Python
  • Data types
  • Data structures
  • Mutable and Immutable Data Structures
  • List, Subscripting, Nested List
  • Tuple, Use cases
  • String Manipulation
  • Dictionary
  • Control flow
  • Functions
  • Hands on Session
  • Summary and Conclusion
  • Modules
  • User Define Modules
  • using import
  • using from
  • Built In Modules
  • Object Oriented Programming
  • Classes and Objects
  • The “self” keyword
  • Methods and Attributes
  • Constructor
  • Object Variable and Class Variable
  • Class Inheritance
  • Hands on Session
  • Summary and Conclusion
  • NumPy for numerical operations
  • Pandas for data manipulation and analysis
  • Handling and preparing data for generative models
  • Hands on Session
  • Summary and Conclusion
  • Basics of TensorFlow for building models
  • Keras as a high-level API for neural networks
  • Installing and setting up the environment
  • TensorFlow Programming
  • Hands on Session
  • Summary and Conclusion
  • Basics of GAN architecture
  • Building and training a simple GAN
  • Common challenges and solutions
  • TensorFlow’s Python API
  • Use TF-GAN Estimators to quickly train a GAN
  • Hands on Session
  • Summary and Conclusion
  • Introduction to autoencoders
  • Variational inference and VAEs
  • Building and training VAEs
  • Autoencoder Demo
  • Train the basic autoencoder
  • Hands on Session
  • Summary and Conclusion
  • Building conditional generative models
  • Applications in image synthesis and manipulation
  • Combining GANs and VAEs
  • Hands on Session
  • Summary and Conclusion
  • Neural style transfer
  • Image generation using generative models
  • Creative applications of generative models
  • Hands on Session
  • Summary and Conclusion
  • Introduction to language models
  • Text generation using GPT-3 and other models
  • Building chatbots and conversational agents
  • Hands on Session
  • Summary and Conclusion