LEAD399 Fall 2026: Difference between revisions
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Created page with "Most information for this course is kept in Canvas. Some information will be compiled here as well for ease of future reuse (so anyone can see the information, whether they are in the course in Canvas or not). =Resources / Readings= Here is a list of resources and readings that are being used in the course. This list will continue to be updated throughout the term." |
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=Resources / Readings= | =Resources / Readings= | ||
Here is a list of resources and readings that are being used in the course. This list will continue to be updated throughout the term. | Here is a list of resources and readings that are being used in the course. This list will continue to be updated throughout the term. | ||
Basic introduction to AI and machine learning | |||
* Google - [https://cloud.google.com/learn/what-is-artificial-intelligence What is AI] | |||
* IBM - [https://www.ibm.com/think/topics/artificial-intelligence What is AI] | |||
Surveys on views of AI | |||
* Pew Research (2026) - [https://www.pewresearch.org/short-reads/2026/07/23/what-americans-think-about-the-global-ai-race/ What Americans Think about The Global AI Race] | |||
* Pew Research (2026) - [https://www.pewresearch.org/wp-content/uploads/sites/20/2026/06/PI_2026.06.17_Americans-and-AI_REPORT.pdf Americans and AI 2026: Chatbots, Smart Devices and Views on Impact] | |||
How LLMs Work | |||
* MIT Management (2023) - [https://mitsloanedtech.mit.edu/ai/basics/how-chatgpt-works-a-non-technical-primer/ How ChatGPT Works: A Non-Technical Primer] | |||
* CSET (2024) - [https://cset.georgetown.edu/article/the-surprising-power-of-next-word-prediction-large-language-models-explained-part-1/ The Surprising Power of Next Word Prediction: Large Language Models Explained, Part 1], and click through for Part 2 and Part 3. | |||
Basics of Prompting LLMs | |||
* Anthropic (2026) - [https://claude.com/blog/best-practices-for-prompt-engineering Best practices for prompt engineering for 2026] | |||
* MLQ AI (2026) - [https://mlq.ai/guides/introduction-to-prompt-engineering/ Prompt Engineering: A Practical Guide for Builders] | |||
* OpenAI (2026) - [https://help.openai.com/en/articles/10032626-prompt-engineering-best-practices-for-chatgpt Prompt engineering best practices for ChatGPT] | |||
Tools/Visualizations | |||
* Chris Hyams - [https://chyams-llm-explorer.hf.space/ LLM Explorer] | |||
* A. Cho et al. (Georgia Tech) - [https://poloclub.github.io/transformer-explainer/ Transformer Explainer] | |||
Revision as of 20:46, 7 September 2026
Most information for this course is kept in Canvas. Some information will be compiled here as well for ease of future reuse (so anyone can see the information, whether they are in the course in Canvas or not).
Resources / Readings
Here is a list of resources and readings that are being used in the course. This list will continue to be updated throughout the term.
Basic introduction to AI and machine learning
- Google - What is AI
- IBM - What is AI
Surveys on views of AI
- Pew Research (2026) - What Americans Think about The Global AI Race
- Pew Research (2026) - Americans and AI 2026: Chatbots, Smart Devices and Views on Impact
How LLMs Work
- MIT Management (2023) - How ChatGPT Works: A Non-Technical Primer
- CSET (2024) - The Surprising Power of Next Word Prediction: Large Language Models Explained, Part 1, and click through for Part 2 and Part 3.
Basics of Prompting LLMs
- Anthropic (2026) - Best practices for prompt engineering for 2026
- MLQ AI (2026) - Prompt Engineering: A Practical Guide for Builders
- OpenAI (2026) - Prompt engineering best practices for ChatGPT
Tools/Visualizations
- Chris Hyams - LLM Explorer
- A. Cho et al. (Georgia Tech) - Transformer Explainer