Secondary Senior Cycle

Data Representation & Data Management

Learn how computers store numbers and text, handle lists/arrays, and see how large datasets power simple AI.

The whole first lesson, as your class sees it. No sign-in needed.

What your school gets

Everything a teacher needs to teach Data Representation & Data Management this year.

In class

  • 9 lessons, ready to teach Each one planned step by step, taught from the board with the same lesson open on each student's device.
  • Quizzes and assessments A short quiz with every lesson.
  • Progress and resultsWhat each student has completed, and how they did.
  • CertificatesFor portfolios, open days and reports home.
  • Try the first lesson: Number Systems: Binary, Decimal, Hex

The course, module by module

9 lessons in 4 modules. The lesson marked Sample opens in full.

1 Number Systems & Encodings 3 lessons · about 3 hours
  1. 1 Number Systems: Binary, Decimal, Hex Sample lesson Quiz
  2. 2 Binary Arithmetic & Conversions Quiz
  3. 3 Character Encoding (ASCII, Unicode) Quiz
2 Data Structures & AI Foundations 2 lessons · about 3 hours
  1. 4 Data Structures Overview (Lists/Arrays) Quiz
  2. 5 Data for AI & Intro to Machine Learning Quiz
3 Ethics & Basic Data Handling 2 lessons · about 2 hours
  1. 6 Introduction to Data Ethics & Privacy Quiz
  2. 7 Basic Data Manipulation in Code Quiz
4 Mini-Project & Practice 2 lessons · about 3 hours
  1. 8 Mini-Project: Data Representation & Management Quiz
  2. 9 Lab Practice & Revision Quiz

What students learn

Duration: 4–5 weeks (≈16–20 class periods) Module Notes: Core lessons total ~10–12 periods, allowing time for a mini-project on data handling. Emphasize the “garbage in, garbage out” principle, linking data quality and ethics—an essential foundation for future AI or data-heavy tasks.

By the end of the course, students can

  1. Convert numbers between binary, decimal, and hexadecimal systems using Python.
  2. Perform binary arithmetic operations and display results in multiple number bases.
  3. Write scripts to display ASCII and Unicode values of user-entered characters.
  4. Implement CRUD operations on lists/arrays to manage data in a simple program.
  5. Analyse a small dataset to perform basic data inspections relevant to AI applications.

What you'll need

Used in some of the lessons. Students can share in groups of two or three.

Chromebook/Laptop/PC

Ready to bring Data Representation & Data Management to your school?

Get in touch to discuss pricing and ordering for your school.

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