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Biomedical and biochemistry
Courses tagged with "Biomedical and biochemistry"
The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language. Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data. Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in SS1085.
Students willing to take the course as part of their graduate program must enrol through Acorn. This course is part of the IMS graduate program.
In this course students will be instructed in how to program in R. Ultimately students will learn how to use R to analyze, process and visualize data. This course is designed for students with little to no experience in programming.
This is a graduate course that can be taken for credit by UofT Biochemistry graduate students. Those students should enrol using ACORN/ROSI.
The goal of this course is to prepare graduate students to perform scientific data analysis using the R programming language. Successful students will learn how to use statistical inference and machine-learning tools to gain insight into data sets, as well as be introduced to techniques and best practises for storing, managing and analyzing data. Topics will include: R programming, version control, modular programming, coding best practices, data analysis, machine learning and scientific visualization.
Classes will be held Tuesdays and Thursdays, 9:00-10:30am, in GB244 and BL205, respectively.
Students willing to take the course as part of their graduate program must enrol through Acorn. This course is part of the IMS graduate program.
In this course students will be instructed in how to program in Python. Ultimately students will learn how to use Python to analyze, process and visualize data. This course is designed for students with little to no experience in programming.
This is a graduate course that can be taken for by UofT Biochemistry graduate students. Those students should enrol using ACORN/ROSI.

Topics include: R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI.
This course is part of the IMS graduate program and due to be current CoViD19 pandemic, it will be taught fully online.
Enrollment for this course is closed.
Topics include: R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI.
This course is part of the IMS graduate program and to be taught at the UofT St. George campus.
Topics include: R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI.
This course is part of the IMS graduate program and to be taught at the UofT St. George campus.
Topics include: R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI.
This course is part of the IMS graduate program and to be taught at the UofT St. George campus.
Topics include: R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI.
This course is part of the IMS graduate program and to be taught at the UofT St. George campus.
In this course data analysis techniques utilizing the R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing. The goal of this course is to prepare graduate students to perform scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data.
Topics include: R programming, version control, automation, modular programming and scientific visualization.
Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI.
This course is part of the IMS graduate program and due to be current CoViD19 pandemic, it will be taught fully online.