ECON 449 is about translating economic questions into something a machine learning model can actually answer — picking the right method for the problem, not just running every algorithm you know. You'll move through supervised and unsupervised techniques in Python, work through lab sessions on fiscal-policy problems, hear from industry guest speakers, and build a group project that ties the methods together on a real economics question. It's a practical capstone-style elective for econ students who want to leave with applied data skills rather than just econometric theory, sitting at the intersection of the department's quantitative track and what firms and central banks are actually hiring for.
→ STARS müfredatı (resmi syllabus)
İlk dosyayı sen atarsan — not, slayt, geçmiş sınav, çözüm, cheat-sheet, ne varsa — defter ekibi öğrenci paylaşımlarından bu dersin notlarını yazar. Drive linki / PDF / ZIP, hepsi olur.
Course Learning Outcomes: Course Learning Outcome Assessment • Have advanced level of fundamental conceptual knowledge so as to consider its reflections in practice. Midterm Quiz Case study discussions • Analyse theoretical knowledge and evaluate its reflections in practice. Term project Case study discussions • Solve a field-related problem both as a team member and as an independent individual Term project • Use field related knowledge to make decisions, implement and apply them. Term project