Discrete mathematics
1–2Discrete mathematics trains the habits computer science depends on — not trivia for exams, but reusable technique for later studios, labs or clinics.
A computer science curriculum is a sequence, not a shopping list. Early courses build shared vocabulary; middle years introduce methods; the final stretch demands a project that can fail in public.
Elective freedom varies: some systems lock professional accreditation hours; others allow wide minors. The courses below are the common spine, not every university's catalogue.
Core courses
Data structures
1–2Data structures trains the habits computer science depends on — not trivia for exams, but reusable technique for later studios, labs or clinics.
Algorithms
1–2Algorithms trains the habits computer science depends on — not trivia for exams, but reusable technique for later studios, labs or clinics.
Computer architecture
2–3Computer architecture trains the habits computer science depends on — not trivia for exams, but reusable technique for later studios, labs or clinics.
Operating systems
2–3Operating systems trains the habits computer science depends on — not trivia for exams, but reusable technique for later studios, labs or clinics.
Databases
2–3Databases trains the habits computer science depends on — not trivia for exams, but reusable technique for later studios, labs or clinics.
Networks
3–4Networks trains the habits computer science depends on — not trivia for exams, but reusable technique for later studios, labs or clinics.
Software engineering
3–4Software engineering trains the habits computer science depends on — not trivia for exams, but reusable technique for later studios, labs or clinics.
Common tracks
Systems
A systems emphasis usually appears after foundations, when students choose seminars, labs or studios that deepen one problem family inside computer science.
AI & ML
A ai & ml emphasis usually appears after foundations, when students choose seminars, labs or studios that deepen one problem family inside computer science.
Security
A security emphasis usually appears after foundations, when students choose seminars, labs or studios that deepen one problem family inside computer science.
Human–computer interaction
A human–computer interaction emphasis usually appears after foundations, when students choose seminars, labs or studios that deepen one problem family inside computer science.
Skill map
Algorithmic thinking94
Systems design88
Debugging90
Math modelling78
Collaboration62
Writing specs70
Algorithmic thinking
Algorithmic thinking is practised weekly in computer science programmes; the percentage is relative strength among skills on this page, not a grade.
Systems design
Systems design is practised weekly in computer science programmes; the percentage is relative strength among skills on this page, not a grade.
Debugging
Debugging is practised weekly in computer science programmes; the percentage is relative strength among skills on this page, not a grade.
Math modelling
Math modelling is practised weekly in computer science programmes; the percentage is relative strength among skills on this page, not a grade.
Collaboration
Collaboration is practised weekly in computer science programmes; the percentage is relative strength among skills on this page, not a grade.
Writing specs
Writing specs is practised weekly in computer science programmes; the percentage is relative strength among skills on this page, not a grade.
How you learn
Lectures & readings
Large-group framing plus primary texts or problem sets that define the week's vocabulary.
Labs / studios / clinics
Supervised practice where mistakes are expected and feedback is specific.
Seminars
Small-group argument; silence is expensive because the group notices.
Capstone / thesis
A public synthesis — defence, exhibition, clinic portfolio or engineered prototype.
Treat the catalogue as a map of practised skills, not a brand promise. The department that grades hard and returns work fast usually teaches more than the one that advertises prestige alone.
Keep exploring
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