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Courses - Fall 2024
ENBC
Biocomputational Engineering
Open Seats as of
07/19/2024 at 10:30 PM
ENBC301
(Perm Req)
Introduction to Biocomputational Engineering
Credits: 1
Grad Meth: Reg, P-F, Aud
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in Biocomputational Engineering major.
Provides practical tools to help Biocomputational Engineering majors to think critically about their goals and career paths and to utilize their major to set their career trajectory.
ENBC311
(Perm Req)
Python for Data Analysis
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in MATH241; and minimum grade of C- in BIOE241 or approved prior study in Matlab.
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in the Biocomputational Engineering major.
Credit only granted for: BIOE489A, BIOE442 or ENBC311.
Provides an introduction to structured programming, computational methods, and data analysis techniques with the goal of building a foundation allowing students to confidently address problems in research and industry. Fundamentals of programming, algorithms, and simulation are covered from a general computer science perspective, while the applied data analysis and visualization portion makes use of the Python SciPy stack.
ENBC322
(Perm Req)
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in ENBC311.
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in the Biocomputational Engineering major.
Credit only granted for: ENEB355 or ENBC322.
Presents an introduction to the techniques for designing efficient computer algorithms and analyzing their complexity using the Python programming language. Students will gain insight into principles and data-structures useful in algorithm design. General topics include asymptotics, sorting and searching, hashing, algorithm design techniques, graph algorithms, and dynamic programming.
ENBC331
(Perm Req)
Applied Linear Systems and Differential Equations
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in MATH246; and minimum grade of C- in BIOE241 or approved prior study in Matlab.
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in the Biocomputational Engineering major.
Credit only granted for: BIOE371 or ENBC331.
Applications of linear algebra and differential equations to bioengineering and biomolecular systems. Designed to instruct students to relate mathematical approaches in bioengineering to their physical systems. Examples will emphasize fluid mechanics, mass transfer, and physiological systems.
ENBC332
(Perm Req)
Statistics, Data Analysis, and Data Visualization
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in MATH246; and minimum grade of C- in BIOE241 or approved prior study in Matlab.
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in the Biocomputational Engineering major.
Credit only granted for: BIOE372, ENBC332 or STAT464.
Instructs students in the fundamentals of probability and statistics through examples in biological phenomenon and clinical data analysis. Data visualization strategies will also be covered.
ENBC341
(Perm Req)
Biomolecular Engineering Thermodynamics
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in MATH246 and PHYS260.
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in the Biocomputational Engineering major.
Credit only granted for: BIOE232, ENBC341 or CHBE301.
A quantitative introduction to thermodynamic analysis of biomolecular systems. The basic laws of thermodynamics will be introduced and explained through a series of examples related to biomolecular systems.
ENBC353
(Perm Req)
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in BSCI170 or BIOE120.
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in the Biocomputational Engineering major.
Credit only granted for: BIOE461 or ENBC353.
Introduces students to the scientific foundation and concepts driving the fast-paced field of synthetic biology. This course aims to apply engineering principles, measurement science, and modern molecular biology to increase understanding of complex biological systems and to develop novel applications that address global challenges in health, manufacturing, energy, agriculture, and the environment. Students will explore the principles and applications of the field via in-depth analysis. The course will also address the societal issues of synthetic biology, and briefly examine interests to regulate research in this area.
ENBC423
(Perm Req)
Applied Computer Vision
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in ENBC311 and ENBC312.
Introduction to the basics and modern deep learning models in the Artificial Intelligence field of computer vision. The course emphasizes applications of computer vision in medical imaging. Computer vision techniques will be demonstrated using software packages implementing bioimage informatics methods.
ENBC425
Imaging and Image Processing
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in ENBC332, ENBC311, and ENBC321.
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in Biocomputational Engineering major.
Instructs students in the fundamentals of biomedical imaging and image processing methods through the physical principles behind major medical imaging modalities, including X-Ray, Computed Tomography (CT), and magnetic resonance imaging (MRI). This course is designed to instruct students in mathematical tools for extracting information from images. There will be real-world assignments and images, which aid in learning complex theories, applications, and coding libraries in a simple way.
ENBC431
(Perm Req)
Finite Element Analysis
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisite: Minimum grade of C- in MATH246.
Restriction: Permission of ENGR-Fischell Department of Bioengineering department; and must be in the Biocomputational Engineering major.
An introduction to the theory, programming and application of the finite element method that is used to solve problems in engineering analysis and design. Modeling, analysis, and design using the FEA software SolidWorks. The objective of the course is to teach the fundamentals of the finite element method with emphasis on the underlying theory, assumption, and modeling issues as well as providing hands-on experience using finite element software to model, analyze, and design systems.