Course Overview:

Course Title: Generative AI Essentials

Course Duration: 12 Weeks (3 Months)

Course Description: This three-month program is designed for individuals aiming to gain essential skills in generative artificial intelligence (AI). Participants will explore core concepts, methodologies, and practical applications of generative AI models. Through hands-on projects, real-world scenarios, and detailed tutorials, participants will develop proficiency in understanding and implementing generative AI techniques.

Detailed Course Outline:

Weeks 1-2: Introduction to Generative AI and Basic Concepts

• Understanding Generative AI

  • Overview of generative AI concepts and applications
  • Differentiating generative models from discriminative models

• Generative Adversarial Networks (GANs)

  • Introduction to GANs and their architecture
  • Use cases for GANs in image and text generation

Weeks 3-4: Variational Autoencoders (VAEs) and Auto-Regressive Models

• Variational Autoencoders (VAEs)

  • Basics of VAEs and latent space representation
  • Generating new data samples using VAEs

• Auto-Regressive Models (e.g., PixelCNN, PixelRNN)

  • Overview of auto-regressive models
  • Application of auto-regressive models in image generation

Weeks 5-6: Natural Language Processing (NLP) with Generative Models

• Language Modeling with Transformers

  • Introduction to transformer models
  • Training language models for text generation

• OpenAI's GPT (Generative Pre-trained Transformer)

  • Understanding the architecture of GPT models
  • Fine-tuning and using pre-trained GPT models for specific tasks

Weeks 7-8: Conditional Generative Models and Style Transfer

• Conditional Generative Models

  • Implementing conditional GANs and VAEs
  • Generating specific content with conditional models

• Style Transfer

  • Techniques for image and text style transfer
  • Applying style transfer in generative AI projects

Weeks 9-10: Deepfake Technology and Ethical Considerations

• Deepfake Technology

  • Understanding the technology behind deepfakes
  • Risks and benefits of deepfake technology

• Ethical Considerations in Generative AI

  • Addressing ethical concerns in generative AI applications
  • Responsible use of generative models

Weeks 11-12: Advanced Topics and Final Project

• Advanced Topics in Generative AI

  • Cutting-edge research and developments in generative AI
  • Exploring advanced generative models

• Final Project: Generative AI Project Implementation

  • Applying learned concepts to a comprehensive real-world generative AI project
  • Designing and implementing a generative AI solution with a focus on a specific use case

Evaluation and Assessment:

• Weekly practical exercises, mid-term projects, and a final project will be used to assess participants' understanding and application of generative AI skills.