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Courses and Programs for

AI and Machine Learning

 

 

 

Get started with AI and machine learning! Featured Programs and Courses Don't know where to start? Compare programs and courses

 

Explore AI and machine learning courses and programs from Canada's top tech university

Whether you're a seasoned professional looking to stay ahead of the curve, or an aspiring data scientist aiming to break into the industry, WatSPEED's comprehensive range of artificial intelligence (AI) and machine learning courses empowers you to harness the power of data like never before.

From understanding complex algorithms to adopting large language models into your work, our programs provide the knowledge and skills necessary to thrive amidst an ongoing data and AI revolution.

Access knowledge from world-renowned professors, researchers, and industry leaders from the University of Waterloo. Browse WatSPEED's machine learning and AI courses and certificate programs.

Featured courses

Python for Machine Learning

Perfect for beginners and professionals! This course is designed to introduce you to data preparation in Python for machine learning applications.

$499.00

Next start date: Jan 13, 2025

Supervised Machine Learning

Gain practical, hands-on experience using Python to implement and evaluate supervised learning algorithms to draw relevant insights and solve problems.

$799.00

Next start date: Feb 24, 2025

Unsupervised Machine Learning

Learn three key concepts and practices of unsupervised machine learning: dimensionality reduction, association rules, and clustering.

$499.00

Next start date: Jan 20, 2025

Neural Networks

Learn the foundational concepts and popular techniques of neural networks, including RNNs, CNNs, and transformers, with hands-on experience using Python to solve real-world problems.

$799.00

Next start date: May 12, 2025

Hands-on Machine Learning

Apply machine learning techniques to real-world problems. Implement a complete machine learning project using Python and relevant libraries from inception to presentation. 

$599

Coming soon!

Featured certificates

Machine Learning Practitioner Certificate

 

Machine Learning Project Specialist Certificate

 

 

Compare machine learning and AI courses and programs

Make your mark in the world of AI and machine learning with professional education offers tailored to meet your needs. Gain a competitive edge and position yourself as a leader in this rapidly evolving field. Based on your interest and experience, choose from the following courses and certificates:

 
Python for Machine Learning: The Essential Starter Kit
Supervised Machine Learning 
Unsupervised Machine Learning 
Neural Networks
Hands-on Machine Learning
Who should enrol
  • Great for those without experience with Python!
  • Individuals in non-technical roles with basic programming and data preparation knowledge, aiming to gain practical, in-demand machine learning and AI skills to stay competitive in the evolving workforce. 
  • Aspiring data analysts, data scientists, or statisticians who are new to machine learning or looking to build their toolkits. 
  • Programmers and developers looking to add Python to their list of programming languages.
  • Individuals in non-technical roles with basic programming and data preparation knowledge, aiming to gain practical, in-demand machine learning and AI skills to stay competitive in the evolving workforce. 
  • Current or aspiring data analysts or data scientists looking to build a machine learning portfolio.
  • Data professionals looking to add machine learning techniques to their domain.
  • Programmers and developers looking to to expand their machine learning knowledge and skills.
  • Individuals in non-technical roles with basic programming and data preparation knowledge, aiming to gain practical, in-demand machine learning and AI skills to stay competitive in the evolving workforce. 
  • Current or aspiring data analysts or data scientists looking to build a machine learning portfolio.
  • Data professionals looking to add machine learning techniques to their domain.
  • Programmers and developers looking to to expand their machine learning knowledge and skills.
  • Individuals in non-technical roles with basic programming and data preparation knowledge, aiming to gain practical, in-demand machine learning and AI skills to stay competitive in the evolving workforce. 
  • Current or aspiring data analysts or data scientists looking to build a machine learning portfolio.
  • Data professionals looking to add machine learning techniques to their domain.
  • Programmers and developers looking for a foundational introduction to neural networks, without needing advanced technical preparation, to explore new opportunities in AI and machine learning applications.
  • Tailored for professionals or students looking to solidify their machine learning skills by applying them to real-world challenges, particularly in collaborative environments. 
Required experience
  • Basic coding skills in any programming language (it does not need to be Python)
Length
  • Seven weeks (approximately five hours per week)
  • Eight weeks (approximately five hours per week)
  • Four weeks (approximately five hours per week)
  • Eight weeks (approximately five hours per week)
  • Eight weeks (approximately five hours per week)
Format
  • Online course with independent learning and live drop-in sessions
  • Online course with independent learning and live drop-in sessions
  • Online course with independent learning and live drop-in sessions
  • Online course with independent learning and optional live drop-in sessions
  • Online collaborative project
What you will learn
  • Learn the key benefits and practical uses of machine learning.
  • Create a portfolio in Jupyter Notebook to showcase your skills.
  • Understand essential data preparation steps.
  • Gain hands-on experience with Python's libraries.
  • Identify when and how to apply supervised learning tools.
  • Use regression for predictions and classification to organize data.
  • Evaluate model performance using various metrics and improve model accuracy through feature selection techniques.
  • Understand the principles and significance of unsupervised learning.
  • Apply dimensionality reduction to manage large datasets.
  • Analyze patterns and relationships using association rule techniques.
  • Discover hidden structures through clustering.
  • Explore the core concepts and architecture of neural networks.
  • Understand transformers, attention mechanisms, and their applications.
  • Learn strategies to mitigate algorithmic bias for secure models.
  • Apply recurrent and convolutional networks and describe reinforcement learning. 
  • Demonstrate data cleaning and preprocessing techniques.
  • Implement complete machine learning projects from start to finish.
  • Critically evaluate models and their performance.
  • Collaborate effectively in teams using Agile project management.
  Visit the Python for Machine Learning webpage and download a brochure. Visit the Supervised Machine Learning webpage. Visit the Unsupervised Machine Learning webpage. Visit the Neural Networks webpage. Visit the Hands-on Machine Learning webpage.

 

 

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