LEAD399 Fall 2026: Difference between revisions
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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 | '''Guides/Standards/etc. at Indiana State University''' | ||
* ISU OIT - [https://sycamoresindstate.sharepoint.com/sites/EMP-OfficeofInformationTechnology/SitePages/Responsible-Use-of-Artificial-Intelligence-(AI).aspx Guidelines for the Responsible Use of Artificial Intelligence (AI)] | |||
'''Basic introduction to AI and machine learning''' | |||
* Google - [https://cloud.google.com/learn/what-is-artificial-intelligence What is AI] | * 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] | * IBM - [https://www.ibm.com/think/topics/artificial-intelligence What is AI] | ||
Surveys on views of 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/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] | * 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 | '''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] | * 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. | * 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 | '''Basics of Prompting LLMs''' | ||
* Anthropic (2026) - [https://claude.com/blog/best-practices-for-prompt-engineering Best practices for prompt engineering for 2026] | * 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] | * 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] | * OpenAI (2026) - [https://help.openai.com/en/articles/10032626-prompt-engineering-best-practices-for-chatgpt Prompt engineering best practices for ChatGPT] | ||
Tools/Visualizations | '''Tools/Visualizations''' | ||
* Chris Hyams - [https://chyams-llm-explorer.hf.space/ LLM Explorer] | * Chris Hyams - [https://chyams-llm-explorer.hf.space/ LLM Explorer] | ||
* A. Cho et al. (Georgia Tech) - [https://poloclub.github.io/transformer-explainer/ Transformer Explainer] | * A. Cho et al. (Georgia Tech) - [https://poloclub.github.io/transformer-explainer/ Transformer Explainer] | ||
* Farhad Bahram - [https://aipedago.gy/brokenbot/ Broken Bot] | |||
=Tips/Tricks= | |||
General advice, etc. with using AI... | |||
'''Do use AI for''' | |||
'''Do NOT use AI for''' | |||
'''Tools/Useful Websites''' | |||
=Assignments / Activities= | |||
The types of assignments and activities we have done... | |||
=Observations= | |||
Observations made by students / faculty based on in-class work... | |||
==Hard for AI Still== | |||
Things that frontier models have failed members of the class on. | |||
* | |||
Latest revision as of 20:42, 12 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.
Guides/Standards/etc. at Indiana State University
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
- Farhad Bahram - Broken Bot
Tips/Tricks
General advice, etc. with using AI...
Do use AI for
Do NOT use AI for
Tools/Useful Websites
Assignments / Activities
The types of assignments and activities we have done...
Observations
Observations made by students / faculty based on in-class work...
Hard for AI Still
Things that frontier models have failed members of the class on.