An introduction to machine learning that focuses on matrix methods and features real-world applications ranging from classification and clustering to denoising and data analysis. Mathematical topics covered include: linear equations, regression, regularization, the singular value decomposition, and iterative algorithms. Machine learning topics include: the lasso, support vector machines, kernel methods, clustering, dictionary learning, neural networks, and deep learning. In addition to the formal course requisites, students are expected to have had exposure to numerical computing (e.g. Matlab, Python, Julia, R). Appropriate for graduate students or advanced undergraduates.
Ideas and techniques for designing, developing, and modifying large software systems. Topics include software engineering processes; requirements and specifications; project team organization and management; software architectures; design patterns; testing and debugging; and cost and quality metrics and estimation. Students will work in large teams on a substantial programming project.
Training in computer programming for competitions: assessing the coding difficulty and complexity of computational problems, recognizing the applicability of known algorithms, fast coding and testing, team work.
Development of the theory, instruments, techniques and practice of modern investment management. Topics include asset pricing and valuation under certainty and uncertainty, portfolio management, determination of interest rates, immunization strategies and derivative securities.
3 credits
SØK1151 Makroøkonomi for ledere
7,5 poeng
Spring
COMP SCI 642 - Introduction to information security
Senior level undergraduate course covering various topics on information security. Covers a wide range of topics, such as cryptographic primitives, security protocols, system security, and emerging topics.
COMP SCI 769 - Advanced Natural Language Processing
Develop algorithms and mathematical models for natural language processing tasks, including text categorization, information retrieval, speech recognition, machine translation, and information extraction. Focus is on the state-of-the-art computational techniques as they are applied to natural language tasks.
TDT4310 Intelligent tekstanalyse og språkforstelse
7,5 poeng
Spring
COMP SCI 766 - Computer Vision
Fundamentals of image analysis and computer vision; image acquisition and geometry; image enhancement; recovery of physical scene characteristics; shape-from techniques; segmentation and perceptual organization; representation and description of two-dimensional objects; shape analysis; texture analysis; goal-directed and model-based systems; parallel algorithms and special-purpose architectures.
Introduces students to the field of virtual reality and focuses on creating immersive, interactive virtual experiences. Survey topics include historical perspectives on virtual reality technology, computer graphics and 3D modeling, human perception and psychology, human computer interaction and user interface design. This course is designed for students with backgrounds in Computer Science, Engineering, Art, Architecture and Design. Students will work in interdisciplinary teams on projects, culminating in a final event that will be showcased to the public. While not an official uisite, the class will be technologically motivated; therefore students should be comfortable learning new software. The class will utilize publicly available game design software which provides tools and services for the creation of interactive content.
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COMP SCI 532 - Matrix Methods in Machine Learning
An introduction to machine learning that focuses on matrix methods and features real-world applications ranging from classification and clustering to denoising and data analysis. Mathematical topics covered include: linear equations, regression, regularization, the singular value decomposition, and iterative algorithms. Machine learning topics include: the lasso, support vector machines, kernel methods, clustering, dictionary learning, neural networks, and deep learning. In addition to the formal course requisites, students are expected to have had exposure to numerical computing (e.g. Matlab, Python, Julia, R). Appropriate for graduate students or advanced undergraduates.
From <https://guide.wisc.edu/courses/comp_sci/>
3 credits
TDT4173 Maskinlæring og case-basert resonnering
7,5 poeng
Fall
COMP SCI 506 - Software Engineering
Ideas and techniques for designing, developing, and modifying large software systems. Topics include software engineering processes; requirements and specifications; project team organization and management; software architectures; design patterns; testing and debugging; and cost and quality metrics and estimation. Students will work in large teams on a substantial programming project.
From <https://guide.wisc.edu/courses/comp_sci/>
3 credits
TDT4290 Kundestyrt prosjekt
15 poeng
Fall
COMP SCI 578 - Contest-level programming
Training in computer programming for competitions: assessing the coding difficulty and complexity of computational problems, recognizing the applicability of known algorithms, fast coding and testing, team work.
From <https://guide.wisc.edu/courses/comp_sci/>
3 credits
TDT4290 Kundestyrt prosjekt
15 poeng
Fall
FINANCE 720 - Investement Theory and Practice
Development of the theory, instruments, techniques and practice of modern investment management. Topics include asset pricing and valuation under certainty and uncertainty, portfolio management, determination of interest rates, immunization strategies and derivative securities.
3 credits
SØK1151 Makroøkonomi for ledere
7,5 poeng
Spring
COMP SCI 642 - Introduction to information security
Senior level undergraduate course covering various topics on information security. Covers a wide range of topics, such as cryptographic primitives, security protocols, system security, and emerging topics.
From <https://guide.wisc.edu/courses/comp_sci/>
3 credits
TTM4134 Informasjonssikkerhet
7,5 poeng
Fall
COMP SCI 769 - Advanced Natural Language Processing
Develop algorithms and mathematical models for natural language processing tasks, including text categorization, information retrieval, speech recognition, machine translation, and information extraction. Focus is on the state-of-the-art computational techniques as they are applied to natural language tasks.
From <https://guide.wisc.edu/courses/comp_sci/>
3 credits
TDT4310 Intelligent tekstanalyse og språkforstelse
7,5 poeng
Spring
COMP SCI 766 - Computer Vision
Fundamentals of image analysis and computer vision; image acquisition and geometry; image enhancement; recovery of physical scene characteristics; shape-from techniques; segmentation and perceptual organization; representation and description of two-dimensional objects; shape analysis; texture analysis; goal-directed and model-based systems; parallel algorithms and special-purpose architectures.
From <https://guide.wisc.edu/courses/comp_sci/>
TDT4265 Computer vision
7,5 poeng
Spring
COMP SCI/DS 579 Virtual Reality
Introduces students to the field of virtual reality and focuses on creating immersive, interactive virtual experiences. Survey topics include historical perspectives on virtual reality technology, computer graphics and 3D modeling, human perception and psychology, human computer interaction and user interface design. This course is designed for students with backgrounds in Computer Science, Engineering, Art, Architecture and Design. Students will work in interdisciplinary teams on projects, culminating in a final event that will be showcased to the public. While not an official uisite, the class will be technologically motivated; therefore students should be comfortable learning new software. The class will utilize publicly available game design software which provides tools and services for the creation of interactive content.
From <https://guide.wisc.edu/courses/comp_sci/>
3 credits
EiT
7,5 poeng
Fall