AI for students in higher education
3 credits, course, bachelor's level, D0048E
Studying in 2025 means learning with AI.
This course equips students and doctoral researchers with research-grade AI workflows that boost productivity while protecting academic integrity, privacy, and reproducibility. You will learn safe, effective patterns for literature discovery, reading and critique, writing and revising, preparing talks and figures, and conducting data analysis—always with transparent citation and verification. We cover model strengths and failure modes, disclosure policies, and how to design a reproducible workflow using notebooks, scripts, and versioned files. Teaching is self-paced with short demonstrations, practical labs, and check-ins with a learning buddy; three optional live sessions enable Q&A, peer exchange, and expert advice (Do´s and Dont’s). Assessment is authentic: automatically graded quizzes plus a reflective report and a final project tailored to your field. With 3 ECTS, support for both Swedish and English, and no prerequisites beyond internet access and a chatbot account, the course meets you where you are. Whether you study humanities, engineering, or the health sciences, you’ll leave with concrete, ethical AI habits that make your work faster, clearer, and more impactful—skills you can apply immediately to assignments, theses, and publications. You will also practice communicating uncertainty, checking AI-generated claims against sources, and collaborating responsibly with peers and supervisors in AI-augmented study environments.
Modules
Format Self-paced with labs, learning-buddy check-ins, and 3 optional live sessions.
Modules
- Possibilities & limits; verification; data privacy & disclosure in research.
- Chat-based research work: search, mapping, critique, drafting/editing, safe citation.
- Presentation prep: storyboarding slides, figures, notes, rehearsal, peer feedback.
- Data analysis tracks: humanities (spreadsheets, word) and engineering (Python/R/Matlab); EDA, plotting, tables/figures, reproducible research.
Format Self-paced with labs, learning-buddy check-ins, and 3 optional live sessions.
3 credits, course, bachelor's level, D0048E
Studying in 2025 means learning with AI.
This course equips students and doctoral researchers with research-grade AI workflows that boost productivity while protecting academic integrity, privacy, and reproducibility. You will learn safe, effective patterns for literature discovery, reading and critique, writing and revising, preparing talks and figures, and conducting data analysis—always with transparent citation and verification. We cover model strengths and failure modes, disclosure policies, and how to design a reproducible workflow using notebooks, scripts, and versioned files. Teaching is self-paced with short demonstrations, practical labs, and check-ins with a learning buddy; three optional live sessions enable Q&A, peer exchange, and expert advice (Do´s and Dont’s). Assessment is authentic: automatically graded quizzes plus a reflective report and a final project tailored to your field. With 3 ECTS, support for both Swedish and English, and no prerequisites beyond internet access and a chatbot account, the course meets you where you are. Whether you study humanities, engineering, or the health sciences, you’ll leave with concrete, ethical AI habits that make your work faster, clearer, and more impactful—skills you can apply immediately to assignments, theses, and publications. You will also practice communicating uncertainty, checking AI-generated claims against sources, and collaborating responsibly with peers and supervisors in AI-augmented study environments.
Modules
Format Self-paced with labs, learning-buddy check-ins, and 3 optional live sessions.
Modules
- Possibilities & limits; verification; data privacy & disclosure in research.
- Chat-based research work: search, mapping, critique, drafting/editing, safe citation.
- Presentation prep: storyboarding slides, figures, notes, rehearsal, peer feedback.
- Data analysis tracks: humanities (spreadsheets, word) and engineering (Python/R/Matlab); EDA, plotting, tables/figures, reproducible research.
Format Self-paced with labs, learning-buddy check-ins, and 3 optional live sessions.
Kontakt
Foteini Liwicki
- Associate Professor
- 0920-491004
- foteini.liwicki@ltu.se
- Foteini Liwicki
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