IBM
AI Workflow: Feature Engineering and Bias Detection
IBM

AI Workflow: Feature Engineering and Bias Detection

This course is part of IBM AI Enterprise Workflow Specialization

Taught in English

Mark J Grover
Ray Lopez, Ph.D.

Instructors: Mark J Grover

4,178 already enrolled

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

4.4

(68 reviews)

Advanced level
Designed for those already in the industry
12 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

10 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.4

(68 reviews)

Advanced level
Designed for those already in the industry
12 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 IBM AI Enterprise Workflow 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 2 modules in this course

This module will introduce you to skills required for effective feature engineering in today's business enterprises. The skills are presented as a series of best practices representing years of practical experience.

What's included

6 videos14 readings5 quizzes1 ungraded lab

This module will continue the discussion of skill related to feature engineering for practicing data scientists, with a focus on outliers and the use of unsupervised learning techniques for finding patterns.

What's included

5 videos11 readings5 quizzes1 ungraded lab

Instructors

Instructor ratings
3.9 (12 ratings)
Mark J Grover
13 Courses89,123 learners

Offered by

IBM

Recommended if you're interested in Machine Learning

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Learner reviews

Showing 3 of 68

4.4

68 reviews

  • 5 stars

    58.82%

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    26.47%

  • 3 stars

    8.82%

  • 2 stars

    2.94%

  • 1 star

    2.94%

PL
4

Reviewed on May 3, 2020

NM
5

Reviewed on Jul 5, 2020

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