COM SCI 205
Health Analytics
Computer Science · 4 units · Graduate courses (200-299)
Recommended: statistics and probability, numerical methods, knowledge in programming languages. Applied data analytics course, with focus on healthcare applications. How to properly generate and analyze health data. Project-based course to learn about best practices in health data collection and validation. Exploration of various machine learning and data analytic tools to learn underlying structure of datasets to solve healthcare problems. Different machine learning concepts and algorithms, statistical models, and building of data-driven models. Big data analytics and tools for handling structured, unstructured, and semistructured datasets.
Letter grading.
Requisites
Official UCLA wording
Enforced requisites: courses 31, 180.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
COM SCI 205
- COM SCI 31Introduction to Computer Science I
- COM SCI 180Introduction to Algorithms and Complexity
- COM SCI 32Introduction to Computer Science II
- MATH 61Introduction to Discrete Structures
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.