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Generative AI Game-Based Learning
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Module 1
GenAI Fundamentals for Educators
1
Generative AI vs. Traditional AI & Machine Learning
Distinguish generative AI from traditional AI and machine learning using concrete examples.
2
Generative Models: Modalities and Tools
Categorize types of generative models by modality (text, image, code) and identify representative tools for each.
3
GenAI Glossary for Beginners
Define key GenAI terminology (tokens, parameters, inference, context window) in plain language suitable for beginners.
4
GenAI in the Real World: Applications for Professionals
Identify real-world GenAI applications relevant to working professionals across industries.
5
Understanding Transformers: Attention Is All You Need
Explain the transformer architecture at a conceptual level, including the role of self-attention.
6
The LLM Training Pipeline: Pre-training to RLHF
Describe the LLM training pipeline: pre-training, supervised fine-tuning, and RLHF.
7
Tokenization: How it Works, Impacts Model Behavior, and Affects Cost
Explain how tokenization works and its effect on model behavior and cost.
8
Understanding LLM Limitations
Identify common LLM limitations, including hallucinations, context window constraints, and training data biases.
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