EES1137

Applications qualitatives pour l'analyse des données
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Cours signalées avec « EES1137 »

EES1137 Quantitative Applications for Data Analysis (Winter 2020)

In this course data analysis techniques utilizing Python and 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: Python and 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 EES graduate program and to be taught at the UTSc campus.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 8 janv. 2020
Date de fin: : 3 avr. 2020

EES1137 Quantitative Applications for Data Analysis (Winter 2021)

In this course data analysis techniques utilizing Python and 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: Python and 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 EES graduate program and to be taught at the UTSc campus.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 12 janv. 2021
Date de fin: : 1 avr. 2021

EES1137 Quantitative Applications for Data Analysis (Winter 2022)

In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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: Python and R programming, version control, automation, modular programming and scientific visualization.

Students willing to take the course as part of their graduate program have to enrol through Acorn/ROSI.
This course is part of the EES graduate program and will be taught online this semester.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 11 janv. 2022
Date de fin: : 7 avr. 2022
Nombre de crédits - calcul scientifique: 8
Nombre de crédits - science des données: 28

EES1137 Quantitative Applications for Data Analysis (Winter 2023)

In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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: Python and R programming, version control, automation, modular programming and scientific visualization.

Students willing to take the course as part of their graduate program must enrol through Acorn/ROSI.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 10 janv. 2023
Date de fin: : 6 avr. 2023
Nombre de crédits - calcul scientifique: 8
Nombre de crédits - science des données: 28

EES1137 Quantitative Applications for Data Analysis (Winter 2024)

In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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: Python and R programming, version control, automation, modular programming and scientific visualization.

Students willing to take the course as part of their graduate program must enrol through Acorn/ROSI.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 9 janv. 2024
Date de fin: : 4 avr. 2024
Nombre de crédits - calcul scientifique: 8
Nombre de crédits - science des données: 28

EES1137 Quantitative Applications for Data Analysis (Winter 2025)

In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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: Python and R programming, version control, automation, modular programming and scientific visualization.

Students willing to take the course as part of their graduate program must enrol through Acorn/ROSI.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 7 janv. 2025
Date de fin: : 3 avr. 2025
Nombre de crédits - calcul scientifique: 8
Nombre de crédits - science des données: 28

EES1137 Quantitative Applications for Data Analysis (Winter 2017)

In this course data analysis techniques utilizing Python and 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: Python and 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 EES graduate program and to be taught at the UTSc campus.

Enseignants: Marcelo Ponce, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 4 janv. 2017
Date de fin: : 31 mars 2017

EES1137 Quantitative Applications for Data Analysis (Winter 2018)

In this course data analysis techniques utilizing Python and 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: Python and 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 EES graduate program and to be taught at the UTSc campus.

Enseignants: Marcelo Ponce, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 5 janv. 2018
Date de fin: : 6 avr. 2018

EES1137 Quantitative Applications for Data Analysis (Winter 2019)

In this course data analysis techniques utilizing Python and 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: Python and 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 EES graduate program and to be taught at the UTSc campus.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date de début: : 9 janv. 2019
Date de fin: : 5 avr. 2019

EES1137 Quantitative Applications for Data Analysis (Winter 2026)

In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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: Python and R programming, version control, automation, modular programming and scientific visualization.

There are three ways to follow this course:

  • As a graduate course for UofT PhD and MSc students. Students that wish to do so, should not self-enrol here, but enrol using ACORN/ROSI.
  • As a SciNet or Alliance user taking the course for SciNet certificate credits; for that, enrol on this site (note: limited spots).
  • As an auditor following along with recordings but not submitting assignments; for this no enrollment is needed.

Enseignants: Alexey Fedoseev, Erik Spence
Catégorie: Data Science (University Credit)
Date: : mar., 6 janv. 2026 - 12:00 am
Nombre de crédits - calcul scientifique: 8
Nombre de crédits - science des données: 28