What is Artificial Intelligence & Machine Learning?
The theory and practice of computer systems that perform tasks that typically require human intelligence, including visual perception, speech recognition, and decision-making. This includes exposure and practical experience in developing and using algorithms to independently learn from and make predictions or decisions based on data.
Artificial Intelligence & Machine Learning Practices
1. Definition
What is AI, ML, neural networks, etc.
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Guide (in text and video formats), hands-on learning |
Intro to Machine Learning |
Weights & Biases |
https://www.wandb.com/classes/intro/overview |
All videos are 10-20 minutes long.
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Online course |
Data Science: Machine Learning |
HarvardX |
https://www.edx.org/course/data-science-machine-learning |
Free to audit, $50 USD for certification.
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2. Ethics
GC ethical considerations, bias, transparency, etc.
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Article |
Using Artificial Intelligence in government means balancing innovation with the ethical and responsible use of emerging technologies |
Government of Canada |
https://open.canada.ca/en/blog/using-artificial-intelligence-government-means-balancing-innovation-ethical-and-responsible |
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Event |
March 6, 2019: Governing AI: Roles for Industry, Research, and Government |
Institute on Governance (IOG)'s Policy Crunch Series |
https://iog.ca/events/series/policycrunch/ |
Free event. Part of IOG's Policy Crunch Series.
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4. Processes & Tools
Data collection, cleaning, visualizations, etc.
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Online course |
Data Science Primer (Chapter 3: Data Cleaning) |
Elite Data Science |
https://elitedatascience.com/data-cleaning |
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5. Types of Learning
Neural networks, reinforcement learning, supervised vs. unsupervised, etc.
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Video |
Neural Networks Explained |
LearnCode.academy |
https://www.youtube.com/watch?v=GvQwE2OhL8I |
12-minute video. Well-paced with examples.
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Course |
Machine Learning (supervised/unsupervised) |
edX |
https://www.edx.org/course/principles-of-machine-learning-python-edition-2 |
Learn about data preparation, feature selection and machine learning algorithms.
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6. Advanced Analysis
Big data, deep learning, social network analysis, etc.
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7. Content Modelling
Structuring content for re-use, content strategy, etc.
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