Goulter Group Learning Center
Learn by working through real examples
Practical courses in Python Programming, Practical AI, Workflow Automation and Spreadsheets for Decisions. Each lesson walks through a worked example, then gives you practice that runs in this page.
Reading and practice are open to everyone. Saving your progress needs an account with course access from your administrator.
Where do you want to start?
Read and fix code
Python Programming
Read, review, debug and build Python, including code an AI assistant wrote, before writing your own.
Beginner friendly. No programming experience needed. 3 courses · 58 lessons · about 25 hours of lessons (planning estimate).
Start with Python FoundationsUse AI and check its work
Practical AI
Ask for results you can check, then accept, repair or reject a response using the evidence.
For noncoders. No external AI account needed. 6 courses · 36 lessons · about 16 hours of lessons (planning estimate).
Find your Practical AI starting pointAutomate a repeating job
Workflow Automation
Plan a job, keep it safe to re-run, and handle a service that fails without watching it run.
Assumes basic Python: functions, loops and dictionaries. 1 course · 18 lessons · about 8 hours of lessons (planning estimate).
Start Practical Workflow AutomationMake a decision with a spreadsheet
Spreadsheets for Decisions
Build a worksheet someone can check, clean the data behind it, and defend the choice it supports.
No programming or paid software needed. 1 course · 18 lessons · about 9 hours of lessons (planning estimate).
Start Spreadsheets for Real Decisions
What the practice looks like
Each sample is copied from a published lesson. Open the lesson to try it yourself.
| Row | C · Learners | E · Formula | E · Cost |
|---|---|---|---|
| 2 | 18 | =C2*$I$2 | 76.5 |
| 3 | 12 | =C3*$I$2 | 51 |
| 4 | 21 | =C4*$I$2 | 89.25 |
I2 · Rate per learner: 4.25
The rate lives in one cell. The dollar signs keep every copied row pointing at it.
base_value = 120000
option_years = 2
option_rate = 0.4
option_value = base_value * option_rate * option_years
ceiling = base_value + option_value
option_rate = 0.6
print(f"Option value: {option_value:,.0f}")
print(f"Ceiling: {ceiling:,.0f}")What does this print?
Check your prediction
Option value: 96,000
Ceiling: 216,000Line 8 rebinds option_rate after both values were computed, so neither printed number changes.
- In A batch of records, plus what the previous run finished
- Each record
- Finished by the previous run: Skip it
- Handled successfully: Add it to processed
- Rejected for good (RecordRejected): Quarantine it and keep going
- Service unavailable or timed out: Retry, at most 2 attempts in all, then stop the run as "partial"
- Out A run record: status, processed, skipped, quarantined and reason
Notice: The workshop includes a workbook. It says nothing about refreshments. Draft: “Refreshments are included.”
Would you keep, revise, or leave the claim unresolved? Explain using the notice.
See the evidence check
Refreshment inclusion is unresolved. A workbook does not establish it, and silence does not prove exclusion. Request confirmation or report the missing information.
All courses
Python Programming
Python Foundations
A beginner-friendly, original Python course for adults and young adults who want to read, review, modify, and debug Python, especially AI-generated Python, rather than memorize syntax.
15 modules · 46 lessons · about 20 h (estimate)
View coursePython Applications
An intermediate course in designing maintainable Python applications with explicit types, asynchronous workflows, dependable tests, and release-ready boundaries.
3 modules · 6 lessons · about 3 h (estimate)
View courseProduction Python Systems
An advanced course in architectural boundaries, reliable state changes, performance evidence, operational resilience, and secure production ownership.
3 modules · 6 lessons · about 3 h (estimate)
View course
Practical AI
AI Foundations and Language
Understand models, context, uncertainty, and the difference between an answer and an action.
2 modules · 6 lessons · about 3 h (estimate)
View coursePrompting, Meaning, and Context
Resolve ambiguity and build requests whose results can be checked.
2 modules · 6 lessons · about 3 h (estimate)
View courseResearch, Evidence, and Critical Judgment
Trace claims to sources and preserve the limits of the evidence.
2 modules · 6 lessons · about 3 h (estimate)
View courseDocuments, Data, and Multimodal Work
Review summaries, tables, charts, and extracted information.
2 modules · 6 lessons · about 3 h (estimate)
View coursePrivacy, Security, and Responsible Use
Identify information boundaries, permissions, and reasons to stop.
2 modules · 6 lessons · about 3 h (estimate)
View courseRepeatable Workflows and Capstones
Combine evidence checks into repeatable work with human approval.
2 modules · 6 lessons · about 4 h (estimate)
View course
Workflow Automation
Practical Workflow Automation
Build a job that runs without you watching it. Map a workflow before automating it, keep every change safe to re-run, organise files and process everyday records, work with a service that is sometimes unavailable, and notice when the job stops running at all. Assumes basic Python functions, loops, and dictionaries. Approximately 8-12 hours including practice, an unvalidated planning estimate rather than a measured completion time.
6 modules · 18 lessons · about 8 h (estimate)
View course
Spreadsheets for Decisions
Spreadsheets for Real Decisions
Build a worksheet someone can trust, then use it to make and defend a decision.
6 modules · 18 lessons · about 9 h (estimate)
View course
How the lessons work
Read before you write
You read, predict, modify and debug a worked example before you author anything from a blank page.
Built for AI-assisted work
Lessons show when to ask an assistant and how to check what it gives you before you rely on it.
Every lesson open from day one
There is a recommended order, but nothing is locked behind a schedule or an exam. Skip what you already know.
The Learning Center does not offer certification, employment placement, or procurement or legal advice. The Python capstone uses public, documented or synthetic sample data, not live government systems, by default.