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Sample curriculum

Python programming

Learn Python through practical scripts, data processing, and reusable application logic.

  • Foundation
  • Live online and in person
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At a glance

Who it’s for

Freshers or teams building a foundation in this technology, with the starting knowledge listed here.

Starting point: Foundation

Bring these foundations

  • Basic computer skills; no Python experience required.
Foundation sessions can be included when needed.

Technologies & tools

  • Python
  • Code editor
  • Jupyter
  • Git
Setup and versions agreed for your environment.

A practical destination

Skills to practise.

The sample path works towards these capabilities. Final goals reflect your team’s starting point and agreed scope.

  1. 01

    Explain Python data, control flow and reusable functions.

  2. 02

    Read, validate and transform files or API data.

  3. 03

    Organise and debug a practical Python programme.

Sample curriculum

Follow the learning route.

Each module connects the concepts to practical work. Open a module to explore both.

01Module 1

Python foundations

Concepts to understand

  • Environment setup and running scripts
  • Types, expressions, and control flow
  • Lists, dictionaries, sets, and tuples

Practical work

Build a small programme with values, collections and control flow. Predict its output and inspect how a change affects it.

Show the result. Explain one decision. Identify what you would improve.
02Module 2

Reusable programs

Concepts to understand

  • Functions, arguments, and modules
  • Classes and object-oriented basics
  • Exceptions and debugging

Practical work

Extract reusable functions and modules from the programme. Add input checks and explain how errors are handled.

Show the result. Explain one decision. Identify what you would improve.
03Module 3

Files & data access

Concepts to understand

  • Reading and writing files
  • CSV, JSON, and API requests
  • Virtual environments and dependencies

Practical work

Read a file or API response, transform its records and write a useful output. Handle missing or malformed data.

Show the result. Explain one decision. Identify what you would improve.
04Module 4

Practical Python

Concepts to understand

  • Data transformation and automation
  • Testing and code organization
  • Project implementation and review

Practical work

Combine the pieces into a practical automation or data-processing task. Review its tests, dependencies and explanation of the result.

Show the result. Explain one decision. Identify what you would improve.

A sample project

Bring the skills together.

Build a Python tool that reads files, validates records, calls an API, and generates a report.

Shorter engagements can focus on selected exercises. A larger, learner-owned capstone can be scoped for a longer programme.

Review the work & reasoning

Four useful questions.

  1. 01

    Does the work meet the agreed requirements?

  2. 02

    Can the learner explain the key decisions and trade-offs?

  3. 03

    What happens with invalid input, failure or an unexpected condition?

  4. 04

    What would they change or explore next?

Designed & delivered by Ragav Kumar V.

Training since 2016 · 100+ batches · 3,000+ professionals trained

Live demonstrations, guided exercises, pair work and project reviews connect the concepts to implementation. We agree the goals, starting knowledge, cohort size, delivery and schedule before shaping the final curriculum.

Shape this for your team

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