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Columbus, United States · Study online with LSBA

AI Project Quality Assurance

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Overview

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Learning outcomes

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Course content

1

Data Validation

2

Model Evaluation

3

Ai Testing Protocols

4

Quality Control Measures

5

Algorithmic Assessment

Career Path

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Key facts

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Why this course

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People also ask

Everything you need to know before you start

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We offer immediate access to our course materials through our open enrollment system. This means:

  • The course starts as soon as you pay the course fee, instantly
  • No waiting periods or fixed start dates
  • Instant access to all course materials upon payment
  • Flexibility to begin at your convenience

This self-paced approach allows you to begin your professional development journey immediately, fitting your learning around your existing commitments.

We offer two flexible learning paths to suit your schedule:

  • Fast Track: Complete in 1 month with 3-4 hours of study per week
  • Standard Mode: Complete in 2 months with 2-3 hours of study per week

You can progress at your own pace and access the materials 24/7.

There are no formal entry requirements for this course. You just need:

  • A good command of English language
  • Access to a computer/laptop with internet
  • Basic computer skills
  • Dedication to complete the course
Ready when you are
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Assessment is done through:

  • Multiple-choice questions at the end of each unit
  • You need to score at least 60% to pass each unit
  • You can retake quizzes if needed
  • All assessments are online

Upon successful completion, you will receive:

  • A digital certificate from London School of Business and Administration
  • Option to request a physical certificate
  • Transcript of completed units
  • Certification is included in the course fee
Open enrolment · Start today

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Why people choose us for their career

Trusted by professionals worldwide

Verified outcomes from learners who finished the course and put it to work.

4.5
Based on 4 learner reviews · 4 countries
98%
Would recommend
100%
Verified learners
2026
Cohort active
Completed from United States
MC
Michael Carter
US · Course completed

The AI Project Quality Assurance course perfectly aligned with my professional development goals. The modules on risk‑based testing and AI model validation gave me a concrete framework I could apply immediately at my job. For instance, I used the checklist template provided in Week 3 to audit a predictive maintenance model, which reduced false‑positive alerts by 12%. The video lectures were concise and the case studies from real‑world enterprises made the material highly relevant. Overall, the course exceeded my expectations and I feel confident delivering higher‑quality AI projects.

SL
Sophie Laurent
CA · Course completed

I loved how hands‑on this course was. The interactive labs let me practice building test suites for a sentiment‑analysis AI, and I actually walked away with a ready‑to‑use test plan that I’ve already shared with my team. The readings were clear and the examples felt right on the mark for the kind of projects we handle in Canada’s fintech sector. The only thing I’d tweak is a bit more focus on post‑deployment monitoring, but overall it helped me meet my learning goal of mastering QA for AI.

FW
Felix Wagner
DE · Course completed

Wow! This course blew me away with its depth and energy. The instructor’s enthusiasm made complex topics like bias detection and explainability easy to grasp. I especially appreciated the live‑coding session where we built a data‑drift detector from scratch – I now use that script in my daily work at a German automotive startup. The supporting PDFs and the curated list of open‑source tools were top‑notch, and the peer‑review assignments gave me valuable feedback. I’m thrilled with the skills I gained and would recommend it to anyone serious about AI quality.

RK
Rahul Kapoor
IN · Course completed

The AI Project Quality Assurance course offered a detailed roadmap for ensuring AI systems meet strict standards. I was particularly impressed by the module on compliance testing, which taught me how to map GDPR requirements to AI model outputs. Using the provided audit worksheet, I conducted a compliance audit for a healthcare AI prototype and identified three critical data‑privacy gaps that were promptly fixed. The course materials – especially the annotated code examples – were thorough and up‑to‑date. My overall learning experience was highly satisfying, and I now feel equipped to lead QA initiatives in my organization.

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Skills gained

Data Analysis
Quality Control
Risk Management
Project Planning
These skills will be developed throughout the course


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Taught in English

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Recently updated!

May 2026