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6 course outlines found
1
COMPSCI 369
: Computational Methods in Interdisciplinary Science2025 Semester One (1253)
Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
2
COMPSCI 369
: Computational Methods in Interdisciplinary Science2024 Semester One (1243)
Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
3
COMPSCI 369
: Computational Methods in Interdisciplinary Science2023 Semester One (1233)
Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.
Prerequisite: COMPSCI 220, and COMPSCI 225 or MATHS 254
4
COMPSCI 369
: Computational Methods in Interdisciplinary Science2022 Semester One (1223)
Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
5
COMPSCI 369
: Computational Biology2021 Semester One (1213)
Computational biology is the development and application of computer algorithms and software to address scientific questions in the biological and life sciences, often using big data. This course includes probabilistic computer modelling, computer-based statistical inference and computer simulation for, and motivated from, the life sciences. It focuses on modelling and analysing real-world biological data with an emphasis on analysing DNA sequence data.
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
Outline is not available yet
6
COMPSCI 369
: Computational Biology2020 Semester One (1203)
Computational biology is the development and application of computer algorithms and software to address scientific questions in the biological and life sciences, often using big data. This course includes probabilistic computer modelling, computer-based statistical inference and computer simulation for, and motivated from, the life sciences. It focuses on modelling and analysing real-world biological data with an emphasis on analysing DNA sequence data.
Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255
Outline is not available yet