Video course · 14 chapters · 22 min · certificate
AI Data Analysis With LLMs: Clean, Explore, Automate
Data analysis with AI: when to use it (the ACHIEVE framework), removing tedious work, safety-net checks, creativity and scale, the DIG framework (describe, introspect, goals), traceability, trends and forecasts, dashboards, multimedia and file automation, utilities and beyond.
What you'll learn
- Decide when AI helps analysis
- Use AI as a safety net and creativity boost
- Apply the DIG framework
- Ensure traceability and replication
- Produce trends, forecasts and dashboards
- Automate files and turn analyses into utilities
Chapters
14 chapters · 21:48-
1:05
01Intro Members
Intro and agenda
Lessons from 11 courses on AI data analysis.
-
1:04
02Framework Members
When to use AI (ACHIEVE)
Using AI for data analysis and human coordination.
-
1:10
03Use Members
Remove tedious work
Cleaning messy sign-up data.
-
1:53
04Use Members
Safety net and creativity
AI checks errors and boosts ideas.
-
1:12
05Use Members
Scale great ideas
Scaling analysis across many inputs.
-
1:33
06Framework Members
The DIG framework
Introducing DIG.
-
2:15
07DIG Members
Step 1: Describe
Exploring data together with AI.
-
2:09
08DIG Members
Step 2: Introspect
Having AI look for issues and questions.
-
1:07
09DIG Members
Step 3: Goals
Giving the AI a clear goal.
-
1:33
10Capabilities Members
Beyond spreadsheets
Analyses that are hard in spreadsheets but easy with AI.
-
1:46
11Rigor Members
Traceability and forecasts
Replicable analyses, trends and forecasts from CSVs.
-
1:59
12Automation Members
Visuals, multimedia and file automation
Dashboards, multimedia workflows, zip files and auto-organizing.
-
1:03
13Utilities Members
Convert to utilities
Turning analysis sequences into reusable utilities.
-
1:59
14Next Members
Beyond analysis
No-code apps, an AI investment agent and wrap-up.
Jobs this course suits
Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.