This course is part of the Machine Learning: Algorithms in the Real World Specialization

4.4
stars
45 ratings

Anna Koop

6,280 already enrolled

Offered By

Machine Learning: Algorithms in the Real World SpecializationAlberta Machine Intelligence Institute

About this Course

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This course synthesizes everything your have learned in the applied machine learning specialization. You will now walk through a complete machine learning project to prepare a machine learning maintenance roadmap. You will understand and analyze how to deal with changing data. You will also be able to identify and interpret potential unintended effects in your project. You will understand and define procedures to operationalize and maintain your applied machine learning model. By the end of this course you will have all the tools and understanding you need to confidently roll out a machine learning project and prepare to optimize it in your business context. 
To be successful, you should have at least beginner-level background in Python programming (e.g., be able to read and code trace existing code, be comfortable with conditionals, loops, variables, lists, dictionaries and arrays). You should have a basic understanding of linear algebra (vector notation) and statistics (probability distributions and mean/median/mode).

This is the final course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute (Amii).

Flexible deadlines

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 4 of 4 in the

Machine Learning: Algorithms in the Real World Specialization

Approx. 11 hours to complete

English

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Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 4 of 4 in the

Machine Learning: Algorithms in the Real World Specialization

Approx. 11 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.88/5 (9 Ratings)

Anna Koop

Senior Scientific Advisor

Alberta Machine Intelligence Institute, University of Alberta

32,800 Learners

4 Courses

Offered by

Alberta Machine Intelligence Institute

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Syllabus - What you will learn from this course

Week1

Week 1

3 hours to complete

Machine Learning Strategy

3 hours to complete

8 videos (Total 42 min), 1 reading, 7 quizzes

Week2

Week 2

2 hours to complete

Responsible Machine Learning

2 hours to complete

6 videos (Total 27 min)

Week3

Week 3

2 hours to complete

Machine Learning in Production & Planning

2 hours to complete

8 videos (Total 33 min)

8 videos

Integrating Info Systems4mUsers Break Things3mTime & Space complexity in production5mWhen do I retrain the model?4mLogging ML Model Versioning4mKnowledge Transfer4mReporting Performance to Stakeholders4mWeekly Summary2m

7 practice exercises

Integrating Info Systems Review5mComplexity in Production Review5mRetrain the Model Review5mML Versioning Review5mKnowledge Transfer Review5mReporting to Stakeholders Review5mMachine Learning in Production and Planning Review30m

Week4

Week 4

5 hours to complete

Care and Feeding of your Machine Learning System

5 hours to complete

9 videos (Total 45 min)

9 videos

MLPL Recap9mPost Deployment Challenges6mQuAM Monitoring and Logging5mQuAM Testing5mQuAM Maintenance3mQuAM Updating5mSeparating Datastack from Production3mDashboard Essentials & Metrics Monitoring5mWeekly Summary1m

7 practice exercises

Post Deployment Challenges Review5mMonitoring & Logging Review5mTesting Review5mMaintenance Review5mUpdating Review5mSeparating Datastack from Production Review5mDashboard Monitoring Review5m

Reviews

4.4

9 reviews

5 stars
71.11%
4 stars
11.11%
3 stars
13.33%
1 star
4.44%

TOP REVIEWS FROM OPTIMIZING MACHINE LEARNING PERFORMANCE

by MBJan 19, 2022

Very good course! I appreciate the opportunity to learn more from Alberta Machine Intelligence Institute. On the downside, Peer-graded Assignment block our progress on the course.

by PZMar 21, 2021

One of the finest courses about Machine Learning Optimization. The course walks you through almost all possible scenarios that will need optimization.

by GVMar 10, 2021

This last course has a great approach of the business applications.

by EGJan 8, 2020

The whole specialization is extremely useful for people starting in ML. Highly recommended!

View all reviews

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.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
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.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Optimizing Machine Learning Performance

About this Course