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Concept and curriculum course
Programming and practical automation

Python Programming and Practical Data Automation

A tested Python automation pipeline and small programming exercises. Raw data is preserved; malformed records and retries are handled; the learner can modify a function unaided.

Beginner50 live hours10 modules
Planned course · requests open

Register your interest. Dates and delivery are confirmed before enrolment opens.

C004 · Curriculum course
A CLEAR LEARNING GOAL

What you will be able to do.

Build understanding, put it into practice and finish with work you can explain.

  • Raw data is preserved; malformed records and retries are handled; the learner can modify a function unaided.

Is this for you?

Beginner learners who can demonstrate the entry competencies listed below. Preparation suggestions are optional.

Before you begin

Create a folder, open a supplied file and submit a named artifact

How you will show your progress

Raw data is preserved; malformed records and retries are handled; the learner can modify a function unaided.

YOUR LEARNING ROUTE

From first principles to applied work.

10 modules

Explain → Demonstration → Guided practice → Review

Planned outline. Lessons, trainer and schedule are confirmed before this course opens.

01240 live minutesSet up Python and understand values

45 min explanation · 45 min demonstration · 105 min practice · 45 min review

    PUT IT INTO PRACTICE

    Run Python locally and trace values and types

    02240 live minutesUse conditions loops functions and modules

    45 min explanation · 45 min demonstration · 105 min practice · 45 min review

      PUT IT INTO PRACTICE

      Write conditions loops functions and small reusable modules

      03360 live minutesWork with collections and file formats

      70 min explanation · 70 min demonstration · 160 min practice · 60 min review

        PUT IT INTO PRACTICE

        Read validated CSV JSON and text fixtures

        04360 live minutesHandle validation exceptions and testing

        70 min explanation · 70 min demonstration · 160 min practice · 60 min review

          PUT IT INTO PRACTICE

          Handle errors and test normal boundary and invalid cases

          05360 live minutesUse tabular data and reproducible transformations

          70 min explanation · 70 min demonstration · 160 min practice · 60 min review

            PUT IT INTO PRACTICE

            Clean tabular data with reproducible transformations

            06360 live minutesQuery a database with safe parameters

            70 min explanation · 70 min demonstration · 160 min practice · 60 min review

              PUT IT INTO PRACTICE

              Use parameterised database queries with source reconciliation

              07240 live minutesCall APIs with error and retry controls

              45 min explanation · 45 min demonstration · 105 min practice · 45 min review

                PUT IT INTO PRACTICE

                Call a mock API with timeouts and bounded retries

                08240 live minutesSchedule scripts and document configuration

                45 min explanation · 45 min demonstration · 105 min practice · 45 min review

                  PUT IT INTO PRACTICE

                  Schedule a local task with safe config and logs

                  09360 live minutesBuild a bounded data-automation capstone

                  70 min explanation · 70 min demonstration · 160 min practice · 60 min review

                    PUT IT INTO PRACTICE

                    Build a new file-to-database automation pipeline

                    10240 live minutesDemonstrate reproducibility and explain edge cases

                    45 min explanation · 45 min demonstration · 105 min practice · 45 min review

                      PUT IT INTO PRACTICE

                      Rerun from clean inputs and repair an unseen data-quality defect

                      MAKE YOUR LEARNING VISIBLE

                      How you will practise and be assessed.

                      The planned assessment checks your result, your judgement and your ability to apply what you learned independently.

                      1. 01

                        Build the promised result

                        Demonstrate the promised artifact

                        WHAT YOUR WORK SHOULD SHOW

                        Raw data is preserved; malformed records and retries are handled; the learner can modify a function unaided.

                      2. 02

                        Test a limit or failure

                        Handle errors and test normal boundary and invalid cases

                        WHAT YOUR WORK SHOULD SHOW

                        The documented failure/uncertainty is visible, and no prohibited action or unsupported success claim occurs.

                      3. 03

                        Apply it independently

                        Independently explain and change one assumption in a tested python automation pipeline and small programming exercises.

                        WHAT YOUR WORK SHOULD SHOW

                        The learner predicts and verifies the change; AI output is not accepted without understanding.

                      KNOW BEFORE YOU COMMIT

                      Where this course stands.

                      Lab assets and supported tool versions are confirmed before teaching

                      Explore the source reference
                      Course ID
                      C004
                      Content
                      Course outline in review
                      Trainer
                      Instructor to be confirmed
                      Enrolment
                      Not open · requests welcome
                      Publication
                      Planned
                      Catalogue date
                      2026-10-15
                      YOUR NEXT LEARNING STEP

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