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Ethics, Bias & Trust in AI

Build ethical AI product judgment to reduce bias, protect trust, and lead responsible AI decisions.

  1. Topics
  2. IT & Software
  3. Artificial Intelligence Basics

Ethics, Bias & Trust in AI

InstructorSchool of AI
Duration8h 52m
Students1,451
Rating0.0 (0)

More Related Topics

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Sponsored
Price
$0.00
$14.99
Coupon
99/100 uses left
Last checked 20h ago
Access
Premium only
Upgrade to unlock this course deal

Coupon history

Comidoc has tracked 17 coupons for this course since 2026, last checked 20h ago. On average, a new coupon appears roughly every 8 days.

Coupon codeDiscountAddedStatusLifetime
SEPTFREE02100% offSep 2, 202603:35 AM UTCExpired~31 daysRan full term
SEPTFREE01100% offSep 2, 202603:32 AM UTCExpired30d 12h
SEPTFREE03100% offSep 2, 202603:15 AM UTCExpired~31 daysRan full term
AUGFREE02100% offAug 1, 202604:06 PM UTCExpired30d 21h
AUGFREE01100% offAug 1, 202604:06 PM UTCExpired30d 21h
AUGFREE03100% offAug 1, 202604:06 PM UTCExpired~31 daysRan full term
Comidoc Analysis

AI Ethics for Product Leaders

Strengths

Lifecycle-based bias analysis

Instruction covers how bias manifests during problem framing, data collection, labeling, and post-deployment stages.

Strategic trade-off frameworks

The curriculum addresses critical business tensions such as accuracy vs fairness and personalization vs privacy.

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Limitations

Lack of applied exercises

The course relies on video-based delivery without explicit projects, labs, or hands-on assignments.

Best suited to

  • Product Owners
  • Business Leaders
  • UX Designers

Less suited to

  • Machine Learning Engineers
  • Software Developers seeking coding instruction

Comidoc Score

5.9/10

Worth considering
Beginner-friendly

Comidoc verdict

The learning path moves from the consequences of AI failure toward integrated governance and leadership. It provides a structured look at how bias enters systems during data collection and model objectives, alongside frameworks for managing business risks like reputational damage.

The curriculum focuses on high-level decision-making and product lifecycle management rather than technical execution or coding. This makes it highly relevant for those overseeing AI strategy but less useful for those building the underlying models.

This course is best suited for non-technical Product Owners, Managers, and Business Leaders looking to integrate ethical oversight into their product development workflows.

Score breakdown

Curriculum depth
8.0

The curriculum provides depth in bias lifecycle analysis and business trade-off frameworks.

Applied learning
3.5

The course is primarily video-based and lacks explicit projects or hands-on exercises.

Clarity & experience
5.0

No substantive sampled-review evidence was available to move teaching clarity away from a neutral assessment.

Currency & reliability
5.0

The available evidence does not establish enough about current reliability to move this dimension away from neutral.

Audience fit
6.5

The curriculum aligns with the stated goals of product owners and business leaders.