Scientific Computing, MSE
Postgraduate
In Philadelphia (USA)
Description
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Type
Postgraduate
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Location
Philadelphia (USA)
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Start date
Different dates available
The MSE in Scientific Computing (SCMP) program at Penn provides multifaceted education in the fundamentals and applications of computational science. This education program provides a rigorous computational foundation for applications to a broad range of scientific disciplines. An education in SCMP combines a comprehensive set of core courses centered on numerical methods, algorithm development for high performance computational platforms, and the analysis of large data, and offers flexibility to specialize in different computational science application areas. Students may elect to pursue a thesis in computationally-oriented research within the School of Engineering and Applied Science.
Facilities
Location
Start date
Start date
Reviews
Subjects
- Computational
- Computational Science
- Computing
Course programme
Introduction to Software Development
Algorithms and Computation
Numerical Methods and Modeling
Big Data Analytics
Applied Machine Learning
Machine Learning
Modern Data Mining
Brain-Computer Interfaces
Network Neuroscience
Mathematical Computation Methods for Modeling Biological Systems
Econometrics I: Fundamentals
Econometrics II: Methods & Models
Econometrics III: Advanced Techniques of Cross-Section Econometrics
Econometrics IV: Advanced Techniques of Time-Series Econometrics
Applied Probability Models for Marketing
Advanced Chemical Kinetics and Reactor Design
Transport Processes II (Nanoscale Transport)
Interfacial Phenomena
Aerodynamics
Nanotribology
Micro and Nano Fluidics
Nanoscale Systems Biology
Fundamental Techniques of Imaging I
Biomedical Image Analysis
Nanotribology
Phase Transformations
Elasticity and Micromechanics of Materials
Software Systems
Software Engineering
Computer Systems Programming
Advanced Programming
Internet and Web Systems
Programming and Problem Solving
Database and Information Systems
Sample Survey Methods
Observational Studies
Computational Linguistics
Machine Perception
Computer Vision & Computational Photography
Advanced Topics in Machine Perception
Computational Learning Theory
Data Mining: Learning from Massive Datasets
Modern Data Mining
Special Topics
Analysis of Algorithms
Advanced Topics in Algorithms and Complexity
Algorithms and Computation
Artificial Intelligence
Learning in Robotics
Modern Regression for the Social, Behavioral and Biological Sciences
Atomic Modeling in Materials Science
Multiscale Modeling of Chemical Systems
Molecular Modeling and Simulations
Computational Science of Energy and Chemical Transformations
Finite Element Analysis
Computational Mechanics
Feedback Control Design and Analysis
Topics In Computational Science and Engineering
Numerical Methods and Modeling
Fundamentals of Linear Algebra and Optimization
Complex Analysis
Intro to Linear, Nonlinear and Integer Optimization
Accelerated Regression Analysis for Business
Stochastic Processes
Modern Convex Optimization
Information Theory
Or a free elective (subject to approval)
Select 2 course units of SCMP 597 Thesis Research or SCMP 599 Independent Study.
Generally, any course in which the primary focus is a physical/chemical/biological/mechanical application area that may be studied computationally is allowed.
Scientific Computing, MSE