MSC1090

Introduction à la biostatistique computationnelle avec R
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Cours signalées avec « MSC1090 »

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

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

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

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