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Introduction to Generative AI

Web Age's one-day Generative AI (Gen AI) training teaches the core concepts and components that power Gen AI. Students explore real-world applications and the challenges and ethical considerations...

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$1,995 USD
Course Code WA3407
Duration 1 day
Available Formats Classroom

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

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 Details

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