Data science and machine learning

Data analysis courses
Related tags:

Courses tagged with "Data science and machine learning"

Principles and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.

Prerequisites: Some Linux command line experience.  Python experience is strongly advised. 

Format: Virtual

Date: Mon, 13 May 2024 - 1:00 pm
Data Science Credits: 3
Principles and uses of relational databases
Date: Wed, 6 May 2015 - 9:30 am
Principles and uses of Relational Databases
Date: Wed, 30 Oct 2013 - 2:00 pm
Two days of mixed lectures and hands-on sessions by SciNet analysts on how to scale up and automate your data-centric analysis using Parallel R and Parallel Python.
Start date: 22 Oct 2014
End date: 23 Oct 2014
The goal of this course is to prepare 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. This course can be taken as Seminars in Translational Research (MSC1010Y-1011Y) for students in the Institute of Medical Science. This course can also be taken by PhD students for graduate credits from the Department of Ecology & Evolutionary Biology (EEB) at the UofT. Interested students from the EEB department should contact Prof. Helen Rodd in advance. The course can also be taken as a mini/modular graduate course by Physics students.
Start date: 11 Oct 2016
End date: 17 Nov 2016

This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts.

Classes will be held, April 22 - May 29, 2025, Tuesdays and Thursdays, 11:00am - 12:00pm.

Format: Virtual

Teacher: Erik Spence
Category: Data Science
Start date: 22 Apr 2025
End date: 29 May 2025
Data Science Credits: 16

Principles and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.

Prerequisites: Some Linux command line experience.  Python experience is strongly advised. 

Format: Virtual

Category: Data Science
Date: Mon, 5 May 2025 - 1:00 pm
Data Science Credits: 3

This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.10; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected.  Lectures will be 11:00am - 12:00pm, Tuesday and Thursdays.  There will be no lectures on May 30 and June 1.
Format: In-person, in the SciNet teaching room (661 University Ave., suite 1140A).  All lectures will be recorded.

Teacher: Erik Spence
Category: Data Science
Start date: 25 Apr 2023
End date: 8 Jun 2023
Data Science Credits: 16

Principles and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.
Format: In-person, but will also be broadcast and recorded.

Category: Data Science
Date: Mon, 29 May 2023 - 1:00 pm
Data Science Credits: 3

This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts.

Classes will be held, April 23 - May 30, Tuesdays and Thursdays, 11:00am - 12:00pm.

Format: Virtual

Teacher: Erik Spence
Category: Data Science
Start date: 23 Apr 2024
End date: 30 May 2024
Data Science Credits: 16

This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.9; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected.  Lectures will be 11:00am - 12:00pm, Tuesday and Thursdays.

Teacher: Erik Spence
Category: Data Science
Start date: 26 Apr 2022
End date: 2 Jun 2022
Data Science Credits: 16
This six- or seven-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected.
Teacher: Erik Spence
Category: Data Science
Start date: 27 Apr 2021
End date: 3 Jun 2021
Principles and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.
Category: Data Science
Start date: 30 Nov 2020
End date: 4 Dec 2020
This seven-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected.
Teacher: Erik Spence
Category: Data Science
Start date: 9 Jun 2020
End date: 30 Jul 2020
This half-day session offers an overview of machine learning tools available in Python. -- Prerequisites: python programming
Teacher: Fei Mao
Category: Data Science
Date: Wed, 26 Jun 2019 - 9:30 am
Data Science Credits: 3
This workshop is part of the 2019 Chemical BioPhysics Symposium.

This workshop will provide an introduction to some of the key methods and concepts in machine learning. We will present and discuss the following topics: - Introduction to machine learning. - Regression. - Bias-variance tradeoff. - Resampling Methods. - Classification algorithms, in general. - Decision trees, kNN, k-means. - Agglomerative clustering.

We will use Python 3, and attendees are expected to be familiar with the Python programming language but extensive programming experience is not required - we will mainly be calling functions in existing packages, not writing large amounts of code.
Teacher: Marcelo Ponce
Category: Data Science
Date: Fri, 3 May 2019 - 10:00 am
Data Science Credits: 3
Principles and uses of relational databases with practical examples using python and sqlite on the Niagara supercomputer.
Category: Data Science
Date: Wed, 1 May 2019 - 1:00 pm
This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 3.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected.
Teacher: Erik Spence
Category: Data Science
Start date: 16 Apr 2019
End date: 6 Jun 2019
This half days session offers an overview of machine learning tools available in Python.
Teacher: Erik Spence
Category: Data Science
Date: Wed, 13 Jun 2018 - 1:30 pm
Principles and uses of relational databases with practical examples using python and sqlite.
Category: Data Science
Date: Wed, 6 Jun 2018 - 12:00 pm
This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts. The programming language will be Python 2.7; experience with Python programming will be assumed. The Keras neural network framework will be used for neural network programming; no experience with Keras will be expected.
Teacher: Erik Spence
Category: Data Science
Start date: 17 Apr 2018
End date: 29 May 2018
Principles and uses of relational databases with practical examples using python and sqlite.
Category: Data Science
Date: Wed, 21 Jun 2017 - 10:00 am
Principles and uses of relational databases with practical examples using python and sqlite.
Category: Data Science
Date: Wed, 4 May 2016 - 9:30 am
This class will introduce students to using Apache Spark on the GPC. The Python interface PySpark will used to access the Spark infrastructure. Students are encouraged to bring a laptop to the class, so as to follow along with the exercises and quizzes. Students will be introduced to the PySpark syntax and commands, techniques for loading and managing data, and various data analysis strategies.
Teacher: Erik Spence
Category: Data Science
Date: Tue, 1 Dec 2015 - 9:00 am
Learn the basic of data research with R, in 4 weeks with 2 lectures per week (mini/modular course).
Teacher: SciNet Team
Category: Data Science
Start date: 6 Oct 2015
End date: 29 Oct 2015