WA3407

Introduction to Generative AI Training

Web Age's 1-day Generative AI (Gen AI) course teaches the core concepts and components that power Gen AI. Students explore real-world applications and understand the challenges and ethical considerations this technology may present. This course also covers machine learning and effective prompting techniques.

This Generative AI course gives students a thorough understanding of this powerful technology through hands-on practice.

Course Details

Duration

1 day

Skills Gained

  • Define generative AI and explain its key concepts and components
  • Identify and discuss real-world uses of generative AI
  • Summarize the limitations and challenges of generative AI
  • Learn about machine learning, effective prompting, and ethical AI through hands-on exercises
Course Outline
  • Understanding Generative AI
    • The Big Picture
      • ML is a subset of AI
      • Deep Learning is a subset of ML
      • GenAI is a subset of Deep Learning
    • Understanding AI Models
      • Foundation Model
      • Generative Models
      • Large Language Models
    • The Mechanism Behind Generation
      • Machine Learning
      • Deep Learning
      • Artificial Neural Networks
      • Hands-on Activity: Training a Model
    • The Balance Between Randomness and Training
    • Tokens and Tokenization
    • Hands-on Activity: Latent Space Exploration
    • Tokens and Model Usage Pricing
  • Real-world Uses of Generative AI
    • Music, Movies, and Art
    • Hands-on Activity: Create with AI Art Tools
    • Game Design and Virtual Worlds
    • 3D Modelling and Prototyping
    • Fashion and Apparel
    • Blogs, Articles, and Scripts
    • Hands-on Activity: Scriptwriting with AI
    • Advertising and Marketing
    • Deepfakes and Their Implications
  • Ethical Considerations and Limitations of AI
    • Ethical Considerations
      • Authenticity and Misinformation
      • Hands-on Activity: Deepfake detection workshop
      • Bias and Fairness
      • Intellectual Property
      • Consent and Privacy
      • Transparency and Accountability
      • Impact on Employment
      • Environmental Impact
      • Safety and Security
      • Regulation and Governance
      • Public Perception and Trust
      • Hands-on Activity: Bias detection workshop
    • Limitations and Challenges of GenAI
      • Training Needs Data
      • Computational Costs
      • Quality and Realism
      • Detection of AI-Generated Content