Coursera
MOOC / Non-credit
0
Applied Mathematics in Bioengineering
About this course
Covers and emphasizes practical applications of linear algebra, statistics, complex analysis, and signal processing in bioengineering. Students develop fluency with matrix decompositions, statistical inference and curve fitting, complex-number representations of signals, linear time-invariant systems, and Fourier analysis, and apply these tools to representative biomedical problems.
B
75/100
CourseAsk score
- What the provider tells you
- 24/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- fluency with matrix decompositions
- understanding of statistical inference
- ability to perform curve fitting
- knowledge of complex-number representations of signals
- applying Fourier analysis to biomedical issues
Machine Learning
#statistical inference
#statistics
#mathematics
#linear algebra
#signal processing
#bioengineering
#complex analysis
#matrix decompositions
#curve fitting
#Fourier analysis
$49.00
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