Alberta Machine Intelligence Institute
Introduction to Applied Machine Learning
Alberta Machine Intelligence Institute

Introduction to Applied Machine Learning

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

Taught in English

Some content may not be translated

Anna Koop

Instructor: Anna Koop

24,323 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.7

(732 reviews)

|

99%

Intermediate level
Some related experience required
6 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

5 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.7

(732 reviews)

|

99%

Intermediate level
Some related experience required
6 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Machine Learning: Algorithms in the Real World Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

This week, you will learn about what machine learning (ML) actually is, contrast different problem scenarios, and explore some common misconceptions about ML. You will apply this knowledge by identifying different components essential to a machine learning business solution.

What's included

12 videos6 readings2 quizzes3 discussion prompts

This week, you will learn how to translate a business need into a machine learning problem. We'll walk through some applied examples so you can get a feel for what makes a well-defined question for your QuAM. Narrowing down your question and making sure you have the data necessary to learn is critical to ML success!

What's included

8 videos4 readings1 quiz2 discussion prompts

This week is all about data. You will learn about data acquisition and understand the various sources of training data. We'll talk about how much data you need and what pitfalls might arise, including ethical issues.

What's included

9 videos2 readings1 quiz2 discussion prompts

This week you will learn about the Machine Learning Process Lifecycle (MLPL). After understanding the definitions and components of the MLPL you will analyze the application of the MLPL on a case study.

What's included

7 videos2 readings1 quiz2 discussion prompts

Instructor

Instructor ratings
4.7 (188 ratings)
Anna Koop
Alberta Machine Intelligence Institute
5 Courses35,956 learners

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Recommended if you're interested in Machine Learning

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4.7

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