Humanizing Artificial Intelligence

Unlock AI's Full Potential

Understand how AI works and turn it into a teammate you trust and collaborate with.

LLMs: Where did they come from? (8 Modules)

1. Computers and Language

The need to talk to computers

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2. Natural Language Processing

The ability to talk to computers

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3. Rules

The first steps to talk to computers

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4. Statistical Models

The first big evolution in talking to computers

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5. Neural Networks

Thinking like the human brain

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6. Attention Mechanism

Models learn how to pay attention

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7. Transformers

More then meets the... I'll stop

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8. Large Language Models

Large Language Models today

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LLMs: Behind the Scenes (14 Modules)

2. Language Models: What Are They?

Understanding the basics of language models

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3. Large Language Models (LLMs)

Understanding what makes language models 'large'

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4. Small Language Models

Understanding the benefits of smaller, focused models

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5. Data

Understanding the importance of data in LLMs

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6. Relational Databases

Understanding traditional relational databases

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7. Document Databases

Understanding document-oriented databases

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8. Graph Databases

Understanding graph-oriented databases

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9. Vector Databases

Understanding vector databases and their importance for LLMs

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10. What's a Vector?

Understanding vectors and their role in LLMs

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11. Tokens

Understanding how LLMs break down text into tokens

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12. Embeddings

Understanding how meaning is embedded in vectors

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14. Parameters

Understanding how parameters define a model's learning capacity

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15. Pretraining

Understanding how LLMs learn through pretraining

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16. Fine-tuning

Understanding how LLMs are specialized through fine-tuning

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Prompting Pro Tips (6 Modules)

1. Intro

Get oriented to the course and what you'll learn.

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2. Prompting Pitfalls

Common mistakes and how to avoid them.

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3. Prompting Techniques

Advanced techniques for crafting effective prompts.

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4. Prompting Parameters

How to tune parameters for better results.

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5. Prompting Polish

How to polish and refine your prompts for best results.

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6. Prompting Frameworks

Popular frameworks for structuring prompts.

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Prompt Techniques (10 Modules)

1. Zero-Shot Prompting

Using language models without providing examples

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2. One-Shot Prompting

Providing a single example to guide the model's response

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3. Few-Shot Prompting

Using multiple examples to guide the model's understanding

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4. Chain-of-Thought Prompting

Encouraging step-by-step reasoning for complex problems

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5. Meta Prompting

Getting the model to help improve your prompts

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6. Role Play Prompting

Instructing the model to adopt a specific persona

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7. Directional Stimulus Prompting

Using subtle cues to guide the model's tone and style

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8. Prompt Chaining

Breaking complex tasks into sequential prompts

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9. Interview Prompting

Encouraging the model to ask clarifying questions

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10. Prompt Frameworks

Using structured templates for consistent prompt design

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