Biomedical and biochemistry

Cours pour étudiants en médecine et biochimie
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Cours signalées avec « Biomedical and biochemistry »

BCH2203 Introduction to Programming in Python (Winter 2024)

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.

Enseignant: Ramses van Zon
Catégorie: Scientific Computing (University Credit)
Date de début: : 10 janv. 2024
Date de fin: : 17 avril 2024
Nombre de crédits - calcul scientifique: 9

BCH2024 Introduction to Programming with R (Winter 2021)

This course is an introductory course in programming utilizing the R Statistical Language. The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator.
Enseignant: Marcelo Ponce
Catégorie: Scientific Computing (University Credit)
Date de début: : 22 févr. 2021
Date de fin: : 10 mai 2021

BCH2024 Introduction to Programming with R (Apr/May 2020)

This course is an introductory course in programming utilizing the R Statistical Language. The course is restricted to student of the UofT's Biochemistry departments. Students interested should register though their graduate coordinator.
Enseignant: Marcelo Ponce
Catégorie: Scientific Computing (University Credit)
Date de début: : 14 avril 2020
Date de fin: : 21 mai 2020

MSC1090 Introduction to Computational Biostatistics with R (Fall 2023)

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.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 12 sept. 2023
Date de fin: : 30 nov. 2023
Nombre de crédits - calcul scientifique: 8
Nombre de crédits - science des données: 28

BCH2202 Introduction to Programming in R (Winter 2023)

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.

Enseignant: Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 8 févr. 2023
Date de fin: : 26 avril 2023
Nombre de crédits - calcul scientifique: 9
Nombre de crédits - science des données: 9

MSC1090 Introduction to Computational Biostatistics with R (Fall 2022)

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.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 13 sept. 2022
Date de fin: : 29 nov. 2022
Nombre de crédits - calcul scientifique: 8
Nombre de crédits - science des données: 28

BCH2203 Introduction to Programming in Python (Winter 2022)

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.

Enseignant: Ramses van Zon
Catégorie: Data Science (University Credit)
Date de début: : 12 janv. 2022
Date de fin: : 15 avril 2023
Nombre de crédits - calcul scientifique: 9
Nombre de crédits - science des données: 9

MSC1090 Introduction to Computational BioStatistics with R (Fall 2020)

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.

Enseignants: Marcelo Ponce, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 8 sept. 2020
Date de fin: : 26 nov. 2020

BCH2024 Introduction to Programming in Python for Biochemistry (Sept. 2020)

This course is to introduce graduate students to the programming language Python in a biochemistry context. The course will teach the students how to install Python on their laptop and then use Python to perform data analysis, and how to submitting analyses to the Teach cluster at SciNet, to which they will have access during the course. The course consists of twelve hands-on sessions, each lasting one hour, where students bring their own laptops and perform assignments, each of these assignments being due for the following lecture.
Enrollment for this course is closed.
Enseignants: SciNet Team, Ramses van Zon
Catégorie: Data Science (University Credit)
Date de début: : 8 sept. 2020
Date de fin: : 21 oct. 2020

MSC1090 Introduction to Computational BioStatistics with R (Fall 2019)

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 to be taught at the UofT St. George campus.

Enseignants: Marcelo Ponce, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 9 sept. 2019
Date de fin: : 5 déc. 2019

MSC1090 Introduction to Computational BioStatistics with R (Fall 2018)

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 to be taught at the UofT St. George campus.

Enseignants: Marcelo Ponce, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 11 sept. 2018
Date de fin: : 29 nov. 2018

MSC1090 Introduction to Computational BioStatistics (Winter 2018)

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 to be taught at the UofT St. George campus.

Enseignants: Marcelo Ponce, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 9 janv. 2018
Date de fin: : 5 avril 2018

MSC1090 Introduction to Clinical BioStatistics (Quantitative Applications for Data Analysis) (Fall 2017)

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 to be taught at the UofT St. George campus.

Enseignants: Marcelo Ponce, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 12 sept. 2017
Date de fin: : 30 nov. 2017

MSC1090 Introduction to Computational Biostatistics with R (Fall 2021)

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.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 14 sept. 2021
Date de fin: : 2 déc. 2021
Nombre de crédits - calcul scientifique: 8
Nombre de crédits - science des données: 28