What this course is
Students explore the fundamentals of artificial intelligence and how it shapes everyday life. Each session pairs a short, jargon-free lecture with an extended lab where you actually use the tools — for writing, research, data analysis, and creative work — while learning to check AI output for accuracy, bias, and ethical problems.
By the end of the course you will be able to:
- Use AI tools to complete real tasks in writing, research, data analysis, and creative expression.
- Evaluate AI outputs for accuracy, bias, and ethical implications — and justify your judgment.
Lessons
Eight modules across ten sessions. Each lesson page has the session objectives, a minute-by-minute agenda, lab instructions, and homework.
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Module 1
What is AI? Past, Present, and Future
Definitions, machine vs. human intelligence, and the key terms — LLMs, machine learning, neural nets.
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Module 2
Generative AI for Everyday Productivity
Text generation, summarization, and translation for study guides, resumes, and daily work.
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Module 3
Working with AI Images, Audio, and Video
Diffusion models, speech-to-text, text-to-speech — and how to spot a deepfake.
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Module 4
AI and Data: Spreadsheets & Visualization
Using AI in Excel and Google Sheets, basic data literacy, and chart generation.
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Mini-lesson focus
Module 5
AI for Research and Information Gathering
How LLMs search, why they hallucinate, and how to fact-check everything they tell you.
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Module 6
Ethics, Bias, and Responsible AI
Bias, privacy, copyright, and environmental impacts — with hands-on bias experiments.
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Module 7
Automation with AI Assistants
Workflow automation, Zapier, and AI copilots — build an assistant that does a chore for you.
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Module 8
Capstone Showcase
Design, build, and present your own AI-assisted project — a study aid, creative piece, or workflow.
Schedule
| Date | Session | Topic |
|---|---|---|
| Sep 24 | 1 | What is AI? Past, Present, and Future |
| Oct 1 | 2 | Generative AI for Everyday Productivity |
| Oct 8 | 3 | Working with AI Images, Audio, and Video |
| Oct 15 | 4 | AI and Data: Spreadsheets & Visualization |
| Oct 22 | 5 | AI for Research and Information Gathering |
| Oct 29 | 6 | Ethics, Bias, and Responsible AI |
| Nov 5 | 7 | Automation with AI Assistants |
| Nov 12 | 8 | Capstone: project design & workshop |
| Nov 19 | 9 | Capstone: build & feedback session |
| Nov 26 | — | No class — Thanksgiving |
| Dec 3 | 10 | Capstone Showcase — final presentations |
Grading & materials
Letter grade or Pass/No Pass. Assessment is by assignments, class participation, hands-on labs, and the capstone presentation. All course materials are free and open — the recommended companion text is Elements of AI (University of Helsinki), a beginner-friendly online course with no math required. See Resources for the full list.