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Machine learning

Up-skill in the Python programming language for Machine Learning

Learn to utilize Python libraries to solve predictive problems (supervised learning) and data clustering problems (unsupervised learning). Study machine learning techniques such as multiple linear regressions (Ridge and Lasso), generalized linear models and classification, clustering, and dimensionality reduction methods (SVM).

Every field of computing is being impacted by Machine Learning: software engineering, data analysis, and artificial intelligence. This course concludes with an opportunity to test, try, and implement a small freelance coding assignment that can be used in your professional portfolio.

Topics

  • Introduction to Machine Learning
  • Playing with built-in datasets
  • Linear regression
  • Polynomial regression
  • Logistic regression
  • Support vector machines
  • Decision trees and random forests
  • K-nearest neighbours
  • Naive Bayes
  • Clustering models
  • Artificial neural networks and deep learning

 


Western Digital BadgeEarn a Western Digital Badge 

Recognizing your learning achievement when you complete this micro-credential

 


Upon successful completion of this course, students will be able to:

  • Describe how machine learning can be used to create models that interpret large amounts of data
  • Apply machine learning methods and algorithms in the context of real-world problems
  • Explore Machine Learning oriented practical applications of scientific libraries such as SciKit-Learn and TensorFlow
  • Identify how to formulate learning tasks as computational problems and the methods that are designed to solve these problems
  • Design and implement methods for problems in pattern recognition, system identification or predictive analysis
  • Complete a freelance coding assignment to demonstrate proficiency using Python programming language for Machine Learning

 


Financial Assistance
Financial Assistance

This course is eligible for Ontario Student Assistance Program (OSAP) micro-credential funding. Find out if you are eligible.


Python for Machine Learning is a complex, advanced level python course.  A foundational knowledge in mathematics and statistics through prior course work or work experience is required.

Machine learning experience is not required; however we strongly recommend prior experience with Python. If you do not have sufficient prior experience using Python, we strongly recommend that you complete TECH6301 Introduction to Python before you begin.


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Certificates

Applies Towards the Following Certificates

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Register - Select a section to enroll in
Type
Online
Dates
Oct 23, 2023 to Dec 01, 2023
Schedule
Total Hours
30.0
Potential Discount
Instructors

What to Expect

This is a self-directed course offered through the RoboGarden online learning platform. There are opportunities to engage online with your class and instructor during regular weekly webinars.

You can expect to spend approximately five hours of work per week on course requirements.

Real-time Learning

There are six live Zoom sessions in this course.

October 24 - 7:00pm - 9:00pm ET
October 31  - 7:00pm - 9:00pm ET
November 7 - 7:00pm - 9:00pm ET
November 14 - 7:00pm - 9:00pm ET
November 21 - 7:00pm - 9:00pm ET
November 28 - 7:00pm - 9:00pm ET

Completion Requirements

This is a graded course where a complete or incomplete will be issued. Evaluation will be based on participation and completion of course activities.

Course Materials

No textbook required. All course materials are provided. Students will be required to create accounts and use tools typically used in the technology industry like GitHub.

Type
Online
Dates
Mar 11, 2024 to Apr 19, 2024
Schedule
Total Hours
30.0
Potential Discount

What to Expect

This is a self-directed course offered through the RoboGarden online learning platform. There are opportunities to engage online with your class and instructor during regular weekly webinars.

You can expect to spend approximately five hours of work per week on course requirements.

Real-time Learning

There will be six live Zoom sessions for this course. 

March 12 - 7:00pm - 9:00pm ET
March 19 - 7:00pm - 9:00pm ET
March 26 - 7:00pm - 9:00pm ET
April 2 - 7:00pm - 9:00pm ET
April 9 - 7:00pm - 9:00pm ET
April 16 - 7:00pm - 9:00pm ET

Completion Requirements

This is a graded course where a complete or incomplete will be issued. Evaluation will be based on participation and completion of course activities.

Course Materials

No textbook required. All course materials are provided. Students will be required to create accounts and use tools typically used in the technology industry like GitHub.

Type
Online
Dates
Jul 02, 2024 to Aug 09, 2024
Schedule
Total Hours
30.0
Potential Discount

What to Expect

This is a self-directed course offered through the RoboGarden online learning platform. There are opportunities to engage online with your class and instructor during regular weekly webinars.

You can expect to spend approximately five hours of work per week on course requirements.

Real-time Learning

There will be six live Zoom sessions scheduled for this course. 

July 2 - 7:00pm - 9:00pm ET
July 9 - 7:00pm - 9:00pm ET
July 16 - 7:00pm - 9:00pm ET
July 23 - 7:00pm - 9:00pm ET
July 30 - 7:00pm - 9:00pm ET
August 6 - 7:00pm - 9:00pm ET

Completion Requirements

This is a graded course where a complete or incomplete will be issued. Evaluation will be based on participation and completion of course activities.

Course Materials

No textbook required. All course materials are provided. Students will be required to create accounts and use tools typically used in the technology industry like GitHub.

Required