Korea Foundation for Women In Science, Engineering and Technology (WISET)
Career reboot — applied AI training for women in science and engineering
About the program
Someone preparing a career change needs work they can show, not a certificate. What they learn has to end up in a portfolio if it is going to lead anywhere. We designed the eight weeks around that. It starts with AI fundamentals, ethics, and copyright, moves into prompt engineering and workflow automation, goes through document and presentation work, and ends in data analysis and visualization — all pulled together into each participant's own project. Every week included time to present what they had built and take feedback. Instead of learning alone and stopping there, participants explained their work in front of others repeatedly. Job-search sessions and profile strategy came early, tying the learning to a career goal.
What we ran
Eight weeks of building, presenting, and taking feedback every session, designed so a portfolio remains at the end
How the program was designed
Finished work and a portfolio set as the standard of completion, to match the career-change goal
Theory moved to online pre-work, so the in-person sessions went to practice and presentation
Job-search sessions and profile strategy placed early, linking the learning to a career goal
Week by week
[Week 1] AI fundamentals
The Framework Act on Artificial Intelligence, AI ethics and copyright, generative AI and how LLMs work, and prompt structure
[Week 2] Prompt engineering and workflow automation
Comparing tools hands-on, writing and refining structured prompts, and designing automation for repetitive work
[Week 3] Writing work documents with AI
Generating and structuring reports, building presentation decks, and comparing the quality of AI translation and summarization
[Week 4] Data analysis fundamentals
Collecting and preparing data, and verifying the analysis
[Week 5] Visualization and drawing insight
Visualizing the analysis and finishing it as a project deliverable
How it ran
Online pre-work alongside in-person practice sessions
Time for presenting finished work and taking feedback every session, to raise its quality
A pre-survey and QR check-in and check-out to manage attendance and progress
Tool installation and account setup handled at orientation, so the first session did not stall
Gallery
