--- okf_version: "0.2" type: Index title: Generative AI & Prompt Engineering description: >- Self-paced workshop on generative AI and prompt engineering for academic research and education, with modules on setup, teaching, research, and ethics. resource: https://tyson-swetnam.github.io/intro-gpt/ tags: [workshop, prompt-engineering, education, research, ethics] sources: - resource: https://www.go-fair.org/fair-principles/ title: FAIR Data Principles - resource: https://www.gida-global.org/care title: CARE Principles for Indigenous Data Governance generated: by: human:tswetnam at: "2026-08-31T00:00:00Z" verified: - by: human:tswetnam at: "2026-08-31T00:00:00Z" status: stable --- # Generative AI & Prompt Engineering Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License. ![visitors](https://visitor-badge.lithub.cc/badge?page_id=tyson-swetnam.intro-gpt&left_color=black&right_color=green) ![banner](assets/banner3_ai.png){width=1000} ## Welcome Welcome to this **self-paced, asynchronous online workshop** on generative AI and prompt engineering for academic research and education. Generative AI tools are now deeply integrated into how we work, conduct research, teach, and learn. This workshop will help you develop the skills to effectively utilize these powerful tools, focusing on the art of crafting "prompts" — the instructions that guide AI models — and exploring how to integrate AI into daily productivity. !!! Success "Learning Objectives" After completing this workshop, you will be able to: * Understand the current generative AI landscape and how it impacts the workplace and classroom * Create effective prompts for leading AI platforms including Claude, ChatGPT, Gemini, and Copilot * Apply AI tools to enhance teaching, research, and daily productivity * Make informed decisions about when and how to integrate AI into your work * Navigate ethical considerations and responsible AI use in academic contexts ## [:material-calendar-clock: Workshop Agenda & Learning Paths](agenda.md) This workshop is organized into **five main modules** with an estimated **8-12 hours** of content. You can complete them in order or skip to sections most relevant to your needs. | Module | Topic | Time | |--------|-------|------| | **0** | [Getting Started](agenda.md#module-0-getting-started-30-60-minutes) - AI landscape and orientation | 30-60 min | | **1** | [Platform Setup](agenda.md#module-1-platform-setup-1-2-hours) - Claude, ChatGPT, Gemini, Copilot | 1-2 hours | | **2** | [Prompt Engineering & Productivity](agenda.md#module-2-prompt-engineering-productivity-2-3-hours) - Core skills and daily use | 2-3 hours | | **3** | [AI in Education](agenda.md#module-3-ai-in-education-2-3-hours) - Teaching, tutoring, and academic administration | 2-3 hours | | **4** | [AI for Research](agenda.md#module-4-ai-for-research-3-4-hours) - Advanced tools and techniques | 3-4 hours | | **5** | [Ethics & Responsible AI](agenda.md#module-5-ethics-responsible-ai-1-2-hours) - Ethical frameworks and considerations | 1-2 hours | [:material-arrow-right: View the full agenda with detailed topics and learning paths](agenda.md){ .md-button .md-button--primary } ## Quick Start !!! example "Choose Your Path" === "Beginners" New to AI? Start here: 1. [:material-compass: AI Landscape Overview](ai_landscape.md) - Understand the AI ecosystem 2. [:simple-anthropic: Set up Claude](claude.md) or [:fontawesome-brands-openai: ChatGPT](chatgpt.md) - Get your first AI account 3. [:material-pencil: Writing Effective Prompts](prompts.md) - Learn core prompting techniques 4. [:material-scale-balance: Ethics Overview](ethics.md) - Understand responsible AI use === "Educators" Focus on teaching applications: 1. [:material-school: Education Overview](education.md) - AI's role in modern education 2. [:material-human-male-board: Teaching with AI](teaching.md) - Course design and content creation 3. [:material-account-school: AI Tutoring](tutoring.md) - Personalized learning assistance 4. [:material-file-document-alert: Plagiarism & Detection](plagiarism.md) - Academic integrity === "Researchers" Focus on research applications: 1. [:material-flask: Research Overview](research.md) - AI in academic research 2. [:material-chart-bar: Data Analysis](daily-productivity.md#data-analysis-without-writing-code) - AI-powered data analysis without coding 3. [:material-robot: Agentic AI](agentic.md) - Autonomous AI workflows 4. [:material-database-search: RAG](rag.md) - Custom knowledge bases === "Developers" Focus on technical integration: 1. [:simple-githubcopilot: GitHub Copilot](copilot.md) - AI pair programming 2. [:material-palette-swatch: Vibe Coding](vibe.md) - AI-assisted development 3. [:material-link-variant: Model Context Protocol](mcp.md) - Tool integration 4. [:material-api: OpenAI API](chatgpt.md) - Programmatic access ## Prerequisites :material-check: **A computer** with internet connection :material-check: **At least one AI platform account** - Free tiers are available for all major platforms: - [:simple-anthropic: Claude](claude.md) - Free or Pro ($20/month) - [:fontawesome-brands-openai: ChatGPT](chatgpt.md) - Free or Plus ($20/month) - [:simple-google: Google Gemini](gemini.md) - Free or AI Pro ($19.99/month) - [:material-microsoft: Microsoft Copilot](microsoft.md) - Free with Microsoft 365 :material-check: **No prior AI experience required** - This workshop starts with the basics and progresses to advanced topics !!! tip "Platform Recommendations" Not sure which platform to choose? See our [Platform Comparison Guide](choose.md) for detailed feature comparisons, pricing, and use-case recommendations. ## Workshop Sections ### [:material-cog: Setup](claude.md) Get started with major AI platforms. Each guide includes account setup, interface overview, and platform-specific tips. | Platform | Description | |----------|-------------| | [:simple-anthropic: Claude](claude.md) | Anthropic's AI with Projects, Artifacts, and MCP support | | [:fontawesome-brands-openai: ChatGPT](chatgpt.md) | OpenAI's ChatGPT with GPTs, Canvas, and Advanced Voice | | [:simple-google: Gemini](gemini.md) | Google's AI with workspace integration and multimodal capabilities | | [:material-microsoft: Microsoft Copilot](microsoft.md) | AI integrated into Microsoft 365 applications | | [:simple-githubcopilot: GitHub Copilot](copilot.md) | AI pair programming for developers | ### [:material-text-box-edit: Prompt Engineering](prompts.md) Master the core skills for effective AI interaction. | Topic | Description | |-------|-------------| | [:material-pencil: Writing Prompts](prompts.md) | Core techniques: chain-of-thought, few-shot learning, role-based prompting | | [:material-briefcase: Daily Productivity](daily-productivity.md) | AI for emails, writing, summarization, data analysis, and workflow automation | | [:material-palette-swatch: Vibe Coding](vibe.md) | AI-assisted software development, plus code-safety guidance | | [:material-compare: Choosing a Platform](choose.md) | Compare features, pricing, and use cases | ### [:material-school: Education](education.md) Explore how AI can enhance teaching, learning, and academic administration. | Topic | Description | |-------|-------------| | [:material-book-open: Overview](education.md) | AI's transformative role in modern education | | [:material-human-male-board: Teaching with AI](teaching.md) | Course design, content creation, and assessment | | [:material-account-school: AI Tutoring](tutoring.md) | Using AI as a personalized learning assistant | | [:material-account-group: Admissions & Recruiting](admissions.md) | AI for student recruitment and admissions | | [:material-file-document-alert: Plagiarism & Detection](plagiarism.md) | AI detection tools and academic integrity | ### [:material-flask: Research](research.md) Advanced topics for researchers using AI in their work. | Topic | Description | |-------|-------------| | [:material-book-open: Overview](research.md) | AI applications in academic research | | [:material-robot: Agentic AI](agentic.md) | Autonomous AI agents and workflows | | [:material-shield-lock: AI Sandboxes](ai_sandboxes.md) | Safe environments for AI experimentation | | [:simple-jupyter: Jupyter AI](jupyter.md) | AI integration in Jupyter notebooks | | [:material-link-variant: Model Context Protocol](mcp.md) | Claude's MCP for tool integration | | [:simple-google: NotebookLM](notebooklm.md) | Google's AI research assistant | | [:material-server: Ollama](ollama.md) | Running LLMs locally | | [:material-database-search: RAG](rag.md) | Retrieval Augmented Generation for custom knowledge bases | | [:material-api: OpenAI API](chatgpt.md) | Programming with OpenAI's API | | [:hugging: HuggingFace](huggingface.md) | Open-source models and datasets | | [:hugging: Gradio](gradio.md) | Building AI interfaces | | [:material-chart-box: Posit (RStudio)](posit.md) | AI tools for R users | | [:material-microsoft-visual-studio-code: VS Code & AI Tools](vscode.md) | AI extensions for VS Code | | [:material-text-search: Text Mining](text_mining.md) | AI for text analysis and NLP | ### [:material-scale-balance: Ethics](ethics.md) Critical considerations for responsible AI use in academia. | Topic | Description | |-------|-------------| | [:material-book-open: Overview](ethics.md) | Ethical frameworks and principles for AI use | | [:material-scale-unbalanced: Bias](bias.md) | Understanding and mitigating AI bias | | [:material-gavel: Legal](legal.md) | Copyright, privacy, and legal considerations | | [:material-eye: Transparency](transparency.md) | Disclosing AI use and maintaining integrity | | [:material-leaf: Environment](environment.md) | Environmental and health impacts of AI | ### [:material-notebook-edit: Hands-On Tutorials](claude-code.md) Apply your learning with practical case studies and tutorials. | Tutorial | Description | |----------|-------------| | [:simple-anthropic: Claude Code Workflow](claude-code.md) | Complete workflow using Claude Code | | [:material-key: KEYS Internship (BIO5)](tutorials/keys.md) | AI-assisted research skills for BIO5 summer interns | | [:material-presentation: Presentations](tutorials/presentations/overview.md) | Workshop slide decks for classroom delivery | | [:material-hospital-building: Public Health AI Lab](tutorials/publichealth/casestudy.md) | Hands-on lab: SMS triage, outbreak synthesis, chart abstraction | | [:material-map: GIS & Map Making](tutorials/publichealth/gis.md) | Creating maps with AI assistance | ## About This Workshop This workshop is maintained and taught by the [University of New Mexico Center for Advanced Research Computing (CARC)](https://carc.unm.edu/){target=_blank}. CARC's research-computing documentation — high-performance computing, storage, and research software — lives at [unm-carc.github.io/docs](https://unm-carc.github.io/docs/){target=_blank}. The workshop was originally developed at the University of Arizona by the [BIO5 Institute](https://bio5.org/){target=_blank}, [AI2S](https://responsibleai.arizona.edu/ai2s){target=_blank}, & [College of Information Science](https://infosci.arizona.edu){target=_blank}. This website follows the [FAIR](https://www.go-fair.org/fair-principles/){target=_blank} and [CARE](https://www.gida-global.org/care){target=_blank} data principles and hopes to help further open science. All materials are freely available and licensed under [Creative Commons Attribution 4.0](http://creativecommons.org/licenses/by/4.0/). This site is also machine-readable: every page is published in the Open Knowledge Format with a raw markdown source, and an `llms.txt` index is provided — see the [For AI Agents](agents.md) guide. [:material-arrow-right: Get started with the full agenda](agenda.md){ .md-button .md-button--primary }