About this Course

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Intermediate Level
Approx. 7 hours to complete
English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 7 hours to complete
English

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Alberta Machine Intelligence Institute

Syllabus - What you will learn from this course

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Week
1

Week 1

3 hours to complete

Introduction to Machine Learning Applications

3 hours to complete
12 videos (Total 44 min), 6 readings, 2 quizzes
12 videos
Instructor Introduction1m
Introduction to Course 12m
What is Artificial Intelligence and Machine Learning?5m
What about Data Science?3m
The Machine Learning Process4m
The Three Kinds of Machine Learning3m
Classification: What is it and how does it work?3m
Regression: Fitting lines and predicting numbers3m
Unsupervised Learning4m
Reinforcement Learning6m
Weekly Summary1m
6 readings
What about Deep Learning? (supplemental)10m
Fooling Neural Networks (supplemental)10m
How to Curate A Ground Truth For Your Business Dataset (Required)10m
Learning From Multiple Annotators: A Survey (supplemental)10m
Inferring the Ground Truth Through Crowdsourcing (supplemental)10m
Semi Supervised Learning (required)10m
2 practice exercises
Concepts and Definitions20m
Identifying Machine Learning Techniques10m
Week
2

Week 2

2 hours to complete

Machine Learning in the Real World

2 hours to complete
8 videos (Total 34 min), 4 readings, 1 quiz
8 videos
Features and transformations of raw data6m
Farmer Betty and Her Precision Agriculture Plans3m
What to consider when using your QuAM2m
Broad Examples Narrowed Down4m
Identify Business Evaluation4m
Everything is a Proxy4m
Weekly Summary2m
4 readings
A Brief Introduction into Precision Agriculture10m
Farmer Betty Tried Unsupervised Learning (required)10m
Data is Central to Your ML Problem (required)10m
Martin Zinkevich's Rules for ML (supplemental)10m
1 practice exercise
Machine Learning in the Real World Review
Week
3

Week 3

1 hour to complete

Learning Data

1 hour to complete
9 videos (Total 34 min), 2 readings, 1 quiz
9 videos
How Much Data Do I Need?4m
Ethical Issues4m
Bias in Data Sources3m
Noise and Sources of Randomness5m
Image Classification Example3m
Data Cleaning: Everybody's favourite task4m
Why you need to set up a Data Pipeline4m
Weekly Summary1m
2 readings
Data Protection Laws (required)10m
Government readings on data privacy (supplemental)10m
1 practice exercise
Understanding Data for ML
Week
4

Week 4

1 hour to complete

Machine Learning Projects

1 hour to complete
7 videos (Total 35 min), 2 readings, 1 quiz
7 videos
MLPL as experienced by Farmer Betty3m
Exploring the process of problem definition7m
Assessing your QuAM for use in your Business6m
Technically Assessing the Strength of your QuAM6m
Different Kinds of Wrong4m
Weekly Summary2m
2 readings
Machine Learning Process Lifecycle Explained10m
Deep Learning for Identifying Metastatic Breast Cancer (advanced supplemental)10m
1 practice exercise
Understanding Machine Learning Projects

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About the Machine Learning: Algorithms in the Real World Specialization

Machine Learning: Algorithms in the Real World

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