COURSE CONTENT
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Proposed topic: Python Foundations for IT Professionals — Practical Workbook. This is an interest check; the book is not yet available.
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What you will learn
Course outcome
You will build a command-line inventory report that reads a CSV file, validates each row, classifies capacity, writes a separate report, and explains rejected data. You will also build a small independent test suite. The programme begins with running a file and works through values, decisions, collections, loops, functions, exceptions and files. It does not require a cloud account or administrator privileges.
The central project is deliberately modest. A beginner needs to understand every decision in a small working programme before adding network access or automated changes. By the end, you should be able to adapt the input and classification rule without copying a whole new script from an assistant.
Keep a practice folder containing your source, synthetic inputs, output reports and notes. The input files in this course contain fictional host names. Make a prediction before each exercise, then compare it with the observed result. Unexpected results are useful evidence about your mental model.
Four chapters, with practical work
- Run a programme and understand its values
- Make decisions and work with collections
- Read CSV safely and build an auditable pipeline
- Test, explain and extend your report
Applied capability and learning route
Implement and test a pure data-validation function with explicit failure results.
Follow the lessons in order: establish the model, trace the supplied evidence, attempt the case, compare the worked solution, and complete the changed-condition project. The target is intermediate reasoning within this stated scope, not mastery of the entire profession or product. If a prerequisite is unfamiliar, pause and use the linked foundational teaching before attempting the project.
All teaching, explained answers and core synthetic practice are free. Some operational labs require separately available software, a licensed test tenant or an authorized lab; offline completion does not claim hands-on product proficiency.
How to complete this course
Study the worked examples, attempt the exercises before opening solutions, and submit your own project notes. Completion records are self-reported; practical competence requires the stated verification.
What you will learn
- Build a validated CSV capacity report, with independent tests and failure cases.
- Implement and test a pure data-validation function with explicit failure results.
Before you start
- Comfort creating a local practice file and following terminal instructions. Begin with the setup and context checks.
Practice environment
- A local Python interpreter and a new practice directory. No tenant or administrator account is needed.
Tested versions
- See the manuscript and validation record. A successful offline fixture does not validate every operating environment.
Technical review: 2026-10-07
Technical referencePractical project
Build a validated CSV capacity report, with independent tests and failure cases.
Applied transfer project: Add negative values, free greater than total, leading/trailing whitespace and non-finite numeric strings. Python float can represent NaN/infinity, so define and test finiteness explicitly if you accept floats. Write tests for exact threshold and near-threshold values. Explain whether your use case needs decimal arithmetic, and keep that decision separate from output rounding. Submit code, test output and a short contract for accepted inputs.
Check your project
- Reproduce the supplied baseline.
- Explain a boundary or negative case.
- Detect and repair a deliberate defect.
- Submit evidence and state unverified limitations.
- Applied laboratory rubric: five dimensions, 0–2 each; target 8/10 with no zero in main result or safety. Native quiz score is separate.
Use these criteria for self-review. Completing a lesson records your progress; it does not verify code correctness.
Practice files
APPLY THE SKILL
Your practical project
Build a validated CSV capacity report, with independent tests and failure cases. Applied transfer project: Add negative values, free greater than total, leading/trailing whitespace and non-finite numeric strings. Python float can represent NaN/infinity, so define and test finiteness explicitly if you accept floats. Write tests for exact threshold and near-threshold values. Explain whether your use case needs decimal arithmetic, and keep that decision separate from output rounding. Submit code, test output and a short contract for accepted inputs.
Evidence to keep
- Reproduce the supplied baseline.
- Explain a boundary or negative case.
- Detect and repair a deliberate defect.
- Submit evidence and state unverified limitations.
- Applied laboratory rubric: five dimensions, 0–2 each; target 8/10 with no zero in main result or safety. Native quiz score is separate.
Use fictional practice data. Keep your inputs, outputs and explanation of the result. Lesson completion records your progress; it does not verify your project.
PRACTICE MATERIALS
Course downloads
Save the materials before starting your lab. Read source files before running them.
CHECK YOUR KNOWLEDGE