BIOENG145
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BIOENG 145 - Introduction to Machine Learning for Computational Biology
Course Title
Introduction to Machine Learning for Computational Biology
Course Description
Genome-scale experimental data and modern machine learning methods have transformed our understanding of biology. This course investigates classical approaches and recent machine learning advances in genomics including:1)Computational models for genome analysis2)Applications of machine learning to high throughput biological data3)Machine learning for genomic data in healthThis course builds on existing skills to introduce methodologies for probabilistic modeling, statistical learning, and dimensionality reduction, while grounding these methods in understanding genomic information.
Minimum Units
4
Maximum Units
4
Grading Basis
Default Letter Grade; P/NP Option
Instructors
Lareau
American Cultures Requirement
No
Reading and Composition Requirement
None of the Reading and Composition Requirement
Prerequisites
Bio 1A or BioE 11, Math 54, CS61B; CS70 or Math 55 recommended
Repeat Rules
Course is not repeatable for credit.
Credit Restriction Courses
-
Credit Restrictions
Students will receive no credit for BIO ENG 145 after completing BIO ENG 245.
Credit Replacement Courses
-
Deficient Grade Removal
A deficient grade in BIO ENG 145 may be removed by taking BIO ENG 245.
Course Objectives
Student Learning Outcomes
Formats
Lecture, Laboratory
Term
Fall
Weeks
15 weeks
Weeks
15
Lecture Hours
3
Laboratory Hours
3
Outside Work Hours
6