Self-Paced Online Workshop¶
This work is licensed under a Creative Commons Attribution 4.0 International License.
Format¶
This is a self-paced, asynchronous online workshop designed to help academics, researchers, and educators learn to effectively use generative AI tools. All materials are freely available online and can be completed at your own pace.
Time Commitment¶
We recommend dedicating 8-12 hours to complete the full workshop, though you can work through sections as needed based on your interests and experience level.
Creators/Instructors:¶
About¶
This website follows the FAIR and CARE data principles and hopes to help further open science.
Learning Path¶
This workshop is organized into five main modules. You can complete them in order or skip to sections most relevant to your needs.
Module 0: Getting Started (30-60 minutes)¶
If participating in an organized workshop, before you begin, please review our Code of Conduct.
Start here to understand the AI landscape and set up your accounts.
| Topic | Description | Link |
|---|---|---|
| Welcome & Overview | Introduction to the workshop and learning objectives | Welcome |
| AI Landscape | Understanding generative AI, LLMs, and the current ecosystem | AI Landscape |
| Code of Conduct | Community guidelines and ethical AI use | Code of Conduct |
Module 1: Platform Setup (1-2 hours)¶
Set up accounts and learn the basics of major AI platforms. Choose the platforms most relevant to your work.
| Platform | Description | Link |
|---|---|---|
| Claude | Anthropic's Claude AI with MCP support | Claude Setup |
| ChatGPT | OpenAI's ChatGPT Plus and API access | ChatGPT Setup |
| Gemini | Google's Gemini AI with workspace integration | Gemini Setup |
| Microsoft Copilot | Microsoft 365 Copilot integration | Copilot Setup |
| GitHub Copilot | AI pair programming for developers | GitHub Copilot |
| Choosing a Platform | Compare features, pricing, and use cases | Comparison Guide |
Module 2: Prompt Engineering & Productivity (2-3 hours)¶
Learn core skills for effective AI interaction and daily productivity.
| Topic | Description | Link |
|---|---|---|
| Writing Effective Prompts | Core techniques for prompt engineering | Prompt Engineering |
| Daily Productivity | AI for emails, writing, research, and workflow | Daily Productivity |
| Code Interpreters | Using AI for data analysis and visualization | Code Interpreters |
| Vibe Coding | AI-assisted software development | Vibe Coding |
Module 3: AI in Education (2-3 hours)¶
Explore how AI can enhance teaching, learning, and academic administration.
| Topic | Description | Link |
|---|---|---|
| Education Overview | AI's role in modern education | Education Overview |
| Teaching with AI | Course design, content creation, and assessment | Teaching |
| AI Tutoring | Using AI as a personalized learning assistant | Tutoring |
| Admissions & Recruiting | AI for student recruitment and admissions | Admissions |
| Plagiarism & Detection | Understanding AI detection and academic integrity | Plagiarism |
Module 4: AI for Research (3-4 hours)¶
Advanced topics for researchers using AI in their work.
| Topic | Description | Link |
|---|---|---|
| Research Overview | AI applications in academic research | Research Overview |
| Agentic AI | Autonomous AI agents and workflows | Agentic AI |
| AI Sandboxes | Safe environments for AI experimentation | AI Sandboxes |
| Jupyter AI | AI integration in Jupyter notebooks | Jupyter AI |
| Model Context Protocol | Claude's MCP for tool integration | MCP |
| NotebookLM | Google's AI research assistant | NotebookLM |
| Ollama | Running LLMs locally | Ollama |
| RAG (Retrieval Augmented Generation) | Building AI with custom knowledge bases | RAG |
| OpenAI API | Programming with OpenAI's API | OpenAI API |
| HuggingFace | Open-source models and datasets | HuggingFace |
| Gradio | Building AI interfaces | Gradio |
| Posit (RStudio) | AI tools for R users | Posit |
| VS Code & AI Tools | AI extensions for VS Code | VS Code |
| Text Mining | AI for text analysis and NLP | Text Mining |
Module 5: Ethics & Responsible AI (1-2 hours)¶
Critical considerations for responsible AI use in academia.
| Topic | Description | Link |
|---|---|---|
| Ethics Overview | Ethical frameworks for AI use | Ethics Overview |
| Bias | Understanding and mitigating AI bias | Bias |
| Legal Considerations | Copyright, privacy, and legal issues | Legal |
| Transparency | Disclosing AI use and maintaining integrity | Transparency |
Hands-On Tutorials¶
Apply your learning with practical case studies and tutorials.
| Tutorial | Description | Link |
|---|---|---|
| Claude Code Workflow | Complete workflow using Claude Code | Claude Code Tutorial |
| Public Health Case Study | AI for public health research | Public Health |
| GIS & Map Making | Creating maps with AI assistance | Map Making |
Recommended Learning Paths¶
For Beginners:
- Module 0: Getting Started
- Module 1: Set up 1-2 platforms
- Module 2: Focus on Writing Prompts and Daily Productivity
- Module 5: Ethics Overview
For Educators:
- Module 0: Getting Started
- Module 1: Platform Setup
- Module 2: Prompt Engineering
- Module 3: Complete Education section
- Module 5: Ethics & Responsible AI
For Researchers:
- Module 0: Getting Started
- Module 1: Platform Setup
- Module 2: Prompt Engineering & Code Interpreters
- Module 4: Select relevant research topics
- Module 5: Ethics & Responsible AI
- Hands-On Tutorials
Prerequisites¶
To get the most out of this workshop, you'll need:
A computer with internet connection
At least one AI platform account - We recommend starting with:
- ChatGPT (Free or Plus)
- Claude (Free or Pro)
- Google Gemini (Free or Advanced)
- Microsoft Copilot (with Microsoft 365)
Optional for developers: GitHub account with GitHub Copilot access
No prior AI experience required - This workshop starts with the basics and progresses to advanced topics
Code of Conduct¶
This Code of Conduct applies to all Event participants, instructors, and activities during the workshop.
Data Science Institute (DSI) is dedicated to providing professional computational research and educational experiences for all of our users, regardless of domain focus, academic status, educational level, gender/gender identity/expression, age, sexual orientation, mental or physical ability, physical appearance, body size, race, ethnicity, religion (or lack thereof), technology choices, dietary preferences, or any other personal characteristic.
While participating at an Event, we expect you to:
- Interact with others and use GPTs professionally and ethically by complying with our Policies.
- Constructively criticize ideas and processes, not people.
- Follow the Golden Rule (treat others as you want to be treated) when interacting online or in-person with collaborators, trainers, and support staff.
- Comply with this Code in spirit as much as the letter, as it is neither exhaustive nor complete in identifying any and all possible unacceptable conduct.
We do not tolerate harassment of other users or staff in any form (including, but not limited to, violent threats or language, derogatory language or jokes, doxing, insults, advocating for or encouraging any of these behaviors). Sexual language and imagery are not appropriate at any time (excludes Protected Health Information in compliance with HIPAA). Any user violating this Code may be expelled from the platform and the workshop at DSI's sole discretion without warning.
To report a violation of this Code, directly speak to a trainer. If you are not comfortable speaking to a trainer, or the trainer is who you are reporting, email info@cyverse.org with the following information:
- Your contact information
- Names (real, username, pseudonyms) of any individuals involved, and or witness(es) if any.
- Your account of what occurred and if the incident is ongoing. If there is a publicly available record (a tweet, public chat log, etc.), please include a link or attachment.
- Any additional information that may be helpful in resolving the issue.