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Python Certification Preparation

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Purpose and certification boundary
Capability outcome
What competence looks like
Learning system
Before you begin
Module 1 - How Python programs execute
- 1.1 Programs are precise instructions
- 1.2 The read-evaluate-store sequence
- 1.3 Interactive mode and scripts
- 1.4 Reading tracebacks
Practical Lab 1 - Build and diagnose a first script
- Scenario
- Tasks
- Acceptance criteria
Module 2 - Values, types, operators and expressions
- 2.1 Core value types
- 2.2 Operators and precedence
- 2.3 Comparisons and Boolean logic
- 2.4 Conversion is a contract decision
Module 3 - Text, input and output
- 3.1 Strings are ordered sequences
- 3.2 Format output for humans
- 3.3 Validate input before relying on it
Practical Lab 2 - Study planner input validator
Module 4 - Decisions and program paths
- 4.1 Indentation is structure
- 4.2 Design conditions from a decision table
- 4.3 Equality and identity
Module 5 - Iteration and controlled repetition
- 5.1 for loops traverse a sequence or iterable
- 5.2 while loops depend on a changing condition
- 5.3 break, continue and loop else
Practical Lab 3 - Gradebook decision engine
Module 6 - Collections and data modelling
- 6.1 Choose a collection by its guarantees
- 6.2 Mutation and aliasing
- 6.3 Iterate with intention
Module 7 - Functions, scope and error handling
- 7.1 A function is a contract
- 7.2 Local scope protects clarity
- 7.3 Handle expected errors narrowly
Practical Lab 4 - Refactor the planner into functions
Module 8 - Certification strategy, debugging and professional practice
- 8.1 Reason before you select an answer
- 8.2 Time-boxed practice cycle
- 8.3 Debugging protocol
- 8.4 Ethical preparation
Practical Lab 5 - Timed mock build and review
- Scenario
- Constraints
- Review prompts
Capstone - Evidence-led learning tracker
- Required deliverables
Official reference set