Course · 8 chapters

Data Work with AI

Use AI to clean messy data, ask sharper questions, surface hidden patterns, and turn findings into decision-ready stories. Excel examples, vendor-agnostic, 8 chapters, ~3h.

Paidpractitioner8 chapters172 minEnglish + 6 languagesCertificate on completion

What you'll be able to do

  • Turn vague requests into sharp questions
  • Clean messy data with AI formulas
  • Spot anomalies in your data fast
  • Write summaries that drive decisions
  • Build reproducible analysis templates
  • Catch AI hallucinations before they ship

What's inside

  1. 1
    Data Analysts: Start Here

    A 12-minute orientation to the Data Analysts skill path — why it exists, what you will be able to do, how the seven chapters relate, and where to begin

    12 min
  2. 2
    The Modern Analyst's AI Workflow

    Map the complete AI-augmented analysis loop — from question to action — and build habits that make any LLM your daily thinking partner

    22 min
  3. 3
    Asking Better Questions of Data

    Turn vague business requests into precise analytical sub-questions — use AI to decompose, challenge, and sharpen every question before you touch the data

    22 min
  4. 4
    Data Cleaning & Reshaping with AI

    Reclaim the 60-80% of analysis time lost to messy data — use AI to detect anomalies, generate Microsoft Excel cleaning formulas, reshape structures, and validate transformations

    24 min
  5. 5
    Exploratory Analysis with AI

    Let AI surface patterns, correlations, anomalies, and next questions from your data — spend less time staring at spreadsheets and more time finding what matters

    22 min
  6. 6
    Storytelling with Data + AI

    Turn analytical findings into compelling narratives that drive decisions — using AI to draft chart titles, annotations, executive summaries, and slide structures

    24 min
  7. 7
    Reproducible Analysis Patterns with AI

    Make every analysis repeatable, auditable, and hand-off-ready — using AI to document, template, and automate your analytical workflows

    22 min
  8. 8
    Bias, Errors & Hallucinations in Data Work

    Recognize the three failure modes of AI-assisted analysis — systematic bias, wrong outputs, and confident fabrication — and build verification protocols that catch them before they reach stakeholders

    24 min

Frequently asked questions

What will I learn in this course?
You learn to apply AI across the full analysis loop: turning vague requests into precise questions, cleaning and reshaping data in Excel, running exploratory analysis, telling data stories, building reproducible workflows, and catching AI errors. It runs 8 chapters in about 3 hours.
Who is this course for?
It is for working data analysts and business professionals who already analyze data and want to add AI to their daily workflow. The practitioner level assumes you do this work and want to do it faster and with more rigor.
Do I need to code or use a specific AI tool?
No coding is required, and the course is vendor-agnostic, so it works with any large language model rather than one product. Microsoft Excel is the running tool example for cleaning and reshaping data.
How long is it and is there a certificate?
The course runs about 3 hours across 8 chapters: a short orientation plus seven learning chapters. It is a self-paced skill path inside AI Academy by Anthropos, and you earn a certificate of completion when you finish the path.
Is this course free?
No, this is a paid skill path included with an AI Academy subscription.

Earn a certificate

Complete all chapters to receive your certificate of completion.