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

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Anna Koop

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

About this Course

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This course 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 course will introduce you to problem definition and data preparation in a machine learning project.
By the end of the course, you will be able to clearly define a machine learning problem using two approaches. You will learn to survey available data resources and identify potential ML applications. You will learn to take a business need and turn it into a machine learning application. You will prepare data for effective machine learning applications.

This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute.

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Course 1 of 4 in the

Machine Learning: Algorithms in the Real World Specialization

Intermediate Level

Approx. 7 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.

Course 1 of 4 in the

Machine Learning: Algorithms in the Real World Specialization

Intermediate Level

Approx. 7 hours to complete

English

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

Try Coursera for Business

Instructor

Instructor rating

4.71/5 (181 Ratings)

Anna Koop

Senior Scientific Advisor

Alberta Machine Intelligence Institute, University of Alberta

32,522 Learners

4 Courses

Offered by

Alberta Machine Intelligence Institute

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Syllabus - What you will learn from this course

Content Rating99%(1,765 ratings)

Week

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

Introduction to the Applied Machine Learning Specialization3m

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

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

Generalization and how machines actually learn6m

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

Week 3

1 hour to complete

Learning Data

1 hour to complete

9 videos (Total 34 min), 2 readings, 1 quiz

9 videos

Sources of Training Data3m

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

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 Overview5m

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

Reviews

4.7

160 reviews

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2 stars
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TOP REVIEWS FROM INTRODUCTION TO APPLIED MACHINE LEARNING

by SLJun 21, 2020

An excellent introduction to the fascinating world of machine learning and its endless applications. Loved the emphasis on the evaluation of the business prospect of ML as well.

by SKOct 13, 2019

This course will give the actual understanding especially focusing on different types of Machine learning with real examples. I'm so excited to learn more about it.

by AASep 11, 2019

very comprehensive course on applied machine learning. the most interesting information in this course is business needs for ML and what it's requirement to have a good QuAM.

by SROct 8, 2020

I have been teaching Machine Learning for some time now. This course is really good and comprehensively presents the working of machine learning process in a nutshell. Very good introductory course.

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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Introduction to Applied Machine Learning

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