ECON 427
Applied Machine Learning
Economics · 4 units · Graduate professional courses (400-499)
Limited to Master of Applied Economics students. Foundational course with primary application to data analytics. Intended to be accessible to students from backgrounds such as economics or mathematics, and to students from less technical backgrounds. Covers some fundamental topics in machine learning such as Bayesian learning, optimization for learning, metric learning, and various classification, regression, clustering techniques, and other advanced topics. Real-world data-intensive problems.
Letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Preparation: basic understanding of technology principles, basic programming skills, sufficient mathematical background in probability, statistics, and matrix analysis.
BruinTree reads · Preparation
needs reviewconfidence 0.00 · from textBruinTree could not read this requirement — see UCLA’s wording above.
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- · could not read "basic programming skills" (no course number found)
- · could not read "sufficient mathematical background in probability" (no course number found)
- · could not read "statistics" (no course number found)
- · could not read "matrix analysis" (no course number found)
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Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.