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February,2023
7 Feb 10:30 am 12:00 pm

EES1137 Lecture 9

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.
EES1137 - Winter 2023
7 Feb 11:00 am 12:00 pm

Scientific Computing Lecture (PHY1610)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
8 Feb 9:00 am 10:00 am

BCH2202 - Lecture 1

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
8 Feb 10:00 am 11:30 am

Intro to SciNet, Niagara and Mist

In about 90 minutes, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.Format: In person, as well as broadcast and recorded. SciNet Teaching Room
HPC105 - Feb 2023Show in Google map
9 Feb 11:00 am 12:30 pm

EES1137 Lecture 10

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.
EES1137 - Winter 2023
9 Feb 11:00 am 12:00 pm

Scientific Computing Lecture (PHY1510)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
11 Feb 12:00 am

Iris data set problem is due

C++ is a high level programming language that is extremely useful for scientific applications. The language has historically had a bad reputation, but modern C++ is much improved so that your code can be relatively short and elegant. In this workshop we will teach the basics of C++ for people who are familiar with the basics of programming, and we will especially compare and contrast C++ with Python (only the material covered in SCMP142 "Intro to Programming with Python" is required). Knowing multiple programming languages may be a useful skill: while Python is a wonderful programming language, execution speed is often a practical issue for pure Python applications. For applications where this is an issue, coding in C++ can significantly improve performance. As C++ can relatively easily be integrated in a Python project, it is also possible (and common) to code just the bottleneck in that language.Format: In-person, but also will be broadcast and recorded.
SCMP241 - Jan 2023
13 Feb 1:00 pm 4:00 pm

MS Windows Subsystem for Linux

Windows Subsystem for Linux (WSL) is Microsoft's implementation of Linux container on Windows. WSL allows users to run various Linux distributions inside Windows and provides fully functional Linux environments for routine tasks. This course explores the usage of WSL and Docker Desktop on Windows. Format: In-person SciNet Teaching Room
SCMP291 - Feb 2023Show in Google map
14 Feb 10:30 am 12:00 pm

EES1137 Lecture 11

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.
EES1137 - Winter 2023
14 Feb 11:00 am 12:00 pm

Scientific Computing Lecture (PHY1610)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
15 Feb 9:00 am 10:00 am

BCH2202 - Lecture 2

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
16 Feb 10:00 am 11:30 am

EES1137 Lecture 12

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.
EES1137 - Winter 2023
16 Feb 11:00 am 12:00 pm

Scientific Computing Lecture (PHY1510)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
21 Feb 12:30 pm 2:00 pm

Intro to GPU Programming #1

An overview of GPUs and their use in supercomputers. This workshop will explain what GPUs are, and cover the basic ideas of GPU use in scientific computing. We will introduce several GPU programming frameworks, and demonstrate how to accelerate a solution of a science problem using a GPU. Python or C++ could be used for the assignment.Format: In person, but also broadcast. SciNet Teaching Room
HPC133 - Feb 2023Show in Google map
22 Feb 9:00 am 10:00 am

BCH2202 - Lecture 3

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
22 Feb 12:30 pm 2:00 pm

Intro to GPU Programming #2

An overview of GPUs and their use in supercomputers. This workshop will explain what GPUs are, and cover the basic ideas of GPU use in scientific computing. We will introduce several GPU programming frameworks, and demonstrate how to accelerate a solution of a science problem using a GPU. Python or C++ could be used for the assignment.Format: In person, but also broadcast. SciNet Teaching Room
HPC133 - Feb 2023Show in Google map
24 Feb 1:30 pm 3:00 pm

Intro to GPU Programming #3

An overview of GPUs and their use in supercomputers. This workshop will explain what GPUs are, and cover the basic ideas of GPU use in scientific computing. We will introduce several GPU programming frameworks, and demonstrate how to accelerate a solution of a science problem using a GPU. Python or C++ could be used for the assignment.Format: In person, but also broadcast. SciNet Teaching Room
HPC133 - Feb 2023Show in Google map
28 Feb 10:30 am 12:00 pm

EES1137 Lecture 13

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.
EES1137 - Winter 2023
28 Feb 11:00 am 12:00 pm

Scientific Computing Lecture (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
March,2023
1 Mar 9:00 am 10:00 am

BCH2202 - Lecture 4

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
2 Mar 10:00 am 11:30 am

EES1137 Lecture 14

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.
EES1137 - Winter 2023
2 Mar 11:00 am 12:00 pm

Scientific Computing (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
7 Mar 10:30 am 12:00 pm

EES1137 Lecture 15

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.
EES1137 - Winter 2023
7 Mar 11:00 am 12:00 pm

Scientific Computing Lecture (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
8 Mar 9:00 am 10:00 am

BCH2202 - Lecture 5

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
9 Mar 10:00 am 11:30 am

EES1137 Lecture 16

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.
EES1137 - Winter 2023
9 Mar 11:00 am 12:00 pm

Scientific Computing (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
13 Mar 1:00 pm 4:00 pm

Linux Shell Scripting

Learn how to write bash scripts, use environment variables, how to control process, and much more. Requires some linux basic command line experience.Format: In-person, but will also be broadcast and recorded. SciNet Teaching Room
SCMP201 - Mar 2023Show in Google map
14 Mar 10:30 am 12:00 pm

EES1137 Lecture 17

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.
EES1137 - Winter 2023
14 Mar 11:00 am 12:00 pm

Scientific Computing Lecture (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
15 Mar 9:00 am 10:00 am

BCH2202 - Lecture 6

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
15 Mar 10:00 am 11:30 am

Intro to SciNet, Niagara and Mist

In about 90 minutes, learn how to use the SciNet systems Niagara and Mist, from securely logging in to running computations on the supercomputer. Experienced users may still pick up some valuable pointers.Format: TBD (hopefully In-person), but also broadcast and recorded. SciNet Teaching Room
HPC105 - Mar 2023Show in Google map
16 Mar 11:00 am 12:30 pm

EES1137 Lecture 18

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.
EES1137 - Winter 2023
16 Mar 11:00 am 12:00 pm

Scientific Computing (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
21 Mar 10:30 am 12:00 pm

EES1137 Lecture 19

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.
EES1137 - Winter 2023
21 Mar 11:00 am 12:00 pm

Scientific Computing Lecture (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
22 Mar 9:00 am 10:00 am

BCH2202 - Lecture 7

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
23 Mar 11:00 am 12:00 pm

Scientific Computing (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
23 Mar 11:00 am 12:30 pm

EES1137 Lecture 20

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.
EES1137 - Winter 2023
27 Mar 1:00 pm 4:00 pm

Python and High Performance Computing

Parallel programming in Python. We will cover subprocess, numexpr, multiprocessing, MPI, and other parallel-enabling python packages.Format: In person, but also broadcast and recorded. SciNet Teaching Room
HPC111 - Mar 2023Show in Google map
28 Mar 10:30 am 12:00 pm

EES1137 Lecture 21

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.
EES1137 - Winter 2023
28 Mar 11:00 am 12:00 pm

Scientific Computing Lecture (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
29 Mar 9:00 am 10:00 am

BCH2202 - Lecture 8

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
30 Mar 11:00 am 12:30 pm

EES1137 Lecture 22

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.
EES1137 - Winter 2023
30 Mar 11:00 am 12:00 pm

Scientific Computing (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
April,2023
4 Apr 10:30 am 12:00 pm

EES1137 Lecture 23

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.
EES1137 - Winter 2023
4 Apr 11:00 am 12:00 pm

Scientific Computing Lecture (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
5 Apr 9:00 am 10:00 am

BCH2202 - Lecture 9

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.
SciNet Teaching Room
BCH2202 - Winter 2023Show in Google map
6 Apr 11:00 am 12:00 pm

Scientific Computing (2023)

This course is aimed at reducing your struggle in getting started with computational projects, and make you a more efficient computational scientist. Topics include well-established best practices for developing software as it applies to scientific computations, common numerical techniques and packages, and aspects of high performance computing. While we will introduce the C++ language, in one language or another, students should already have some programming experience. Despite the title, this course is suitable for many physical scientists (chemists, astronomers, ...).This is a graduate course that can be taken for graduate credit by UofT PhD and MSc students. Students that wish to do so, should enrol using ACORN/ROSI.
PHY1610 - Winter 2023
6 Apr 11:00 am 12:30 pm

EES1137 Lecture 24

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.
EES1137 - Winter 2023