About this Course
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100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 13 hours to complete

Suggested: 9 hours/week...

English

Subtitles: English

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 13 hours to complete

Suggested: 9 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
4 hours to complete

Machine Learning Strategy

8 videos (Total 42 min), 1 reading, 7 quizzes
8 videos
ML Readiness6m
Risk Mitigation5m
Experimental Mindset5m
Build/Buy/Partner7m
Setting up a Team5m
Understanding and Communicating Change7m
Weekly Summary2m
1 reading
IP questions10m
6 practice exercises
ML Readiness Review10m
Risk Mitigation Review10m
Experimental Mindset Review10m
Build/Buy/Partner Review30m
Setting up a Team Review5m
Communicating Change Review5m
Week
2
1 hour to complete

Responsible Machine Learning

6 videos (Total 27 min), 5 quizzes
6 videos
Positive Feedback Loops & Negative Feedback Loops6m
Metric Design & Observing Behaviours6m
Secondary Effects of Optimization4m
Regulating Concerns3m
Weekly Summary2m
5 practice exercises
AI4Good Review10m
Feedback Loops Review5m
Metric Design Review5m
Secondary effects Review5m
Regulating Concerns Review10m
Week
3
1 hour to complete

Machine Learning in Production & Planning

8 videos (Total 33 min), 6 quizzes
8 videos
Users Break Things3m
Time & Space complexity in production5m
When do I retrain the model?4m
Logging ML Model Versioning4m
Knowledge Transfer4m
Reporting Performance to Stakeholders4m
Weekly Summary2m
6 practice exercises
Integrating Info Systems Review
Complexity in Production Review
Retrain the Model Review
ML Versioning Review
Knowledge Transfer Review
Reporting to Stakeholders Review
Week
4
5 hours to complete

Care and Feeding of your Machine Learning System

9 videos (Total 45 min), 8 quizzes
9 videos
Post Deployment Challenges6m
QuAM Monitoring and Logging5m
QuAM Testing5m
QuAM Maintenance3m
QuAM Updating5m
Separating Datastack from Production3m
Dashboard Essentials & Metrics Monitoring5m
Weekly Summary1m
7 practice exercises
Post Deployment Challenges Review
Monitoring & Logging Review
Testing Review
Maintenance Review
Updating Review
Separating Datastack from Production Review
Dashboard Monitoring Review

Instructor

Avatar

Anna Koop

Senior Scientific Advisor
Alberta Machine Intelligence Institute, University of Alberta

About Alberta Machine Intelligence Institute

The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based research institute that pushes the bounds of academic knowledge and guides business understanding of artificial intelligence and machine learning....

About the Machine Learning: Algorithms in the Real World Specialization

This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application. After completing all four courses, you will have gone through the entire process of building a machine learning project. You will be able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve your results, and deploy it in the real world. You will also be able to anticipate and mitigate common pitfalls in applied machine learning....
Machine Learning: Algorithms in the Real World

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.