Alberta Machine Intelligence Institute

Data for 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

8,168 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.4

(97 reviews)

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

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

14 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.4

(97 reviews)

Intermediate level
Some related experience required
11 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

We all know that data is important for machine learning success, but what does it really look like? What steps do you need to take to get from scattered, unprocessed data to nice clean learning data? This week takes an overarching view to describe how your problem and data needs interact, and what processes need to be in place for successful data preparation.

What's included

11 videos2 readings3 quizzes

Now that you have your data sources identified, you need to bring it all together. This week describes what you need to prepare data overall.

What's included

11 videos4 quizzes

Data is particular to a problem. This week we'll discuss how to turn generic data into successful fuel for specific machine learning projects.

What's included

8 videos2 readings3 quizzes1 programming assignment1 ungraded lab

There are so many ways data can go wrong! This week discussed some of the pitfalls in data identification and processing.

What's included

9 videos4 quizzes

Instructor

Instructor ratings
4.8 (19 ratings)
Anna Koop
Alberta Machine Intelligence Institute
5 Courses36,028 learners

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Recommended if you're interested in Machine Learning

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Learner reviews

Showing 3 of 97

4.4

97 reviews

  • 5 stars

    59.79%

  • 4 stars

    26.80%

  • 3 stars

    9.27%

  • 2 stars

    1.03%

  • 1 star

    3.09%

NH
5

Reviewed on Jul 16, 2020

PN
5

Reviewed on Dec 29, 2020

PA
4

Reviewed on Jun 8, 2020

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