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Certification

Certification in LLM-Driven Data Cleaning, Exploration, and Automation

Get certified in AI Data Analysis with LLMs. Prove you can clean messy data, ask better prompts, surface insights in minutes, and automate repeat reports into reusable tools. Deliver high-value wins and analyst-grade results at speed.

Exam of 10 to 20 questionsCertificate for LinkedInBeginner · Intermediate
OperationsProduct developmentExecutives and strategyFinance
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The exam

Take the certification exam

Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.

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What the exam covers

2 questions from each of the 14 chapters of the course

20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.

  1. 01Intro and agenda1:05
  2. 02When to use AI (ACHIEVE)1:04
  3. 03Remove tedious work1:10
  4. 04Safety net and creativity1:53
  5. 05Scale great ideas1:12
  6. 06The DIG framework1:33
  7. 07Step 1: Describe2:15
  8. 08Step 2: Introspect2:09
  9. 09Step 3: Goals1:07
  10. 10Beyond spreadsheets1:33
  11. 11Traceability and forecasts1:46
  12. 12Visuals, multimedia and file automation1:59
  13. 13Convert to utilities1:03
  14. 14Beyond analysis1:59
About the course

AI Data Analysis With LLMs: Clean, Explore, Automate (Video Course) is a certification that shows you how to ask questions of your data and get concrete answers in minutes. Along the way, you'll increase productivity, make better decisions, gain a competitive edge, and keep your career future-proof,with the adaptability, growth, and earning potential that come with it. Enroll to learn a fast, hands-on workflow that treats AI like a junior analyst, uses DIG to cut guesswork, applies ACHIEVE to spot high-value wins, and turns one-off analyses into reusable tools.

This certification covers the following topics:

  • Mindset: Treat AI Like a Junior Analyst
  • When to Use AI: The ACHIEVE Framework
  • Structured Workflow: The DIG Framework (Description, Introspection, Goal)
  • Guardrails: Avoiding Hallucinations and Errors
  • Automated File Organization
  • Traceability and Replication (including the Traceability Document)
  • Analysis Across Diverse and Multimedia Data
  • Turning Conversation Into Code
  • Beyond Analysis: Reports, Dashboards, and Apps
  • Practical Prompt Patterns You Can Reuse
  • Common Pitfalls and How to Avoid Them
  • From Insights to Influence: Turning Analysis Into Impact