STATS 413
Machine Learning and Artificial Intelligence
Statistics · 4 units · Graduate professional courses (400-499)
Limited to Master of Applied Statistics students. Introduction to modern machine-learning methods and their applications in artificial intelligence (AI), including deep learning methods with neural networks, boosting methods based on trees, kernel methods such as support vector machines. Use of Python and PyTorch to implement some of the methods.
Letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Recommended preparation: linear algebra, calculus, basic computer programming knowledge.
BruinTree reads · Recommended
needs reviewconfidence 0.00 · from textBruinTree could not read this requirement — see UCLA’s wording above.
- · could not read "linear algebra" (no course number found)
- · could not read "calculus" (no course number found)
- · could not read "basic computer programming knowledge" (no course number found)
- · no course reference could be read from this requisite
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.
STATS 413
- STATS 414From Predictive Artificial Intelligence to Generative Artificial Intelligence
1 course lists this as a requisite. The whole downstream is here — 1 course over 1 level. Every course here opens its own tree.