An applied Swiss-inspired curriculum combining algorithmic rigour, systems architecture, digital trust and practical engineering capability for modern technology leaders.
The Foundation in Data Literacy at Brookfield School of Computing is engineered to provide deep competency across core computer science, systems design, and targeted domain applications. Students develop fluency in software craftsmanship, distributed architectures, algorithm optimization, and data governance.
Instruction balances rigorous theoretical foundations with practical code repositories, laboratory simulations, and ethical technology review aligned with modern international computing standards.
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| FDA011 | Foundations of Data Literacy & Algorithmic Problem Solving | Theory | Develop computational thinking, structured problem decomposition and algorithmic problem solving in Data Literacy. |
| FDA012 | Structured Programming for Data Literacy with Python | Practical | Write, debug and test clean Python scripts, functions, loops and data structures for Data Literacy applications. |
| FDA013 | Mathematics & Quantitative Foundations for Data Literacy | Theory | Solve linear equations, functions, coordinate geometry and basic probability for computing applications in Data Literacy. |
| FDA014 | Computer Systems Architecture & Terminal Basics in Data Literacy | Practical | Navigate Linux file systems, manage system processes and write command-line scripts in Bash for Data Literacy. |
| FDA015 | Academic English & Technical Communication in Data Literacy | Theory | Develop academic writing, technical reporting, presentation skills and literature research habits in Data Literacy. |
| FDA016 | Interactive Web Foundations & Digital Interfaces for Data Literacy | Practical | Create structured web pages using HTML5, CSS3 styling and JavaScript interactivity for Data Literacy interfaces. |
| FDA017 | Data Representation & Information Structures in Data Literacy | Theory | Analyze binary representation of numbers, character encodings (ASCII/UTF-8) and data modeling in Data Literacy. |
| FDA018 | Relational Databases & SQL Essentials Lab for Data Literacy | Practical | Create relational database tables, insert records and write structured SQL SELECT queries with joins for Data Literacy. |
| FDA019 | Digital Ethics, Security Awareness & Independent Study in Data Literacy | Theory | Analyze cyber hygiene principles, intellectual property rules and ethical online academic practices in Data Literacy. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| FDA021 | Object-Oriented Design & Problem Solving in Data Literacy | Theory | Model software concepts using object-oriented principles, classes, objects, encapsulation and inheritance in Data Literacy. |
| FDA022 | Practical Coding Workshop & Lab in Data Literacy | Practical | Build multi-module programs in Python or Java incorporating modular design patterns and unit tests for Data Literacy. |
| FDA023 | Discrete Mathematics, Logic & Set Theory Foundations for Data Literacy | Theory | Apply truth tables, propositional logic statements, sets and basic graph representations to Data Literacy. |
| FDA024 | Software Engineering Tools, Git & Version Control in Data Literacy | Practical | Initialize Git repositories, create branches, resolve merge conflicts and collaborate via GitHub in Data Literacy. |
| FDA025 | Computer Networks, Web Protocols & Internet Systems in Data Literacy | Theory | Analyze IP addressing, DNS resolution, HTTP request-response cycles and network routers for Data Literacy. |
| FDA026 | Data Analysis, Spreadsheets & Introductory Pandas Lab for Data Literacy | Practical | Clean tabular data, compute summary statistics and generate charts using Excel and Python Pandas in Data Literacy. |
| FDA027 | Operating Systems Fundamentals & System Administration in Data Literacy | Theory | Explain CPU process scheduling, memory allocation, file systems and operating system security for Data Literacy. |
| FDA028 | Practical Application Mini-Project in Data Literacy | Practical | Develop a functional software application or analytical dashboard solving a realistic problem in Data Literacy. |
| FDA029 | Foundation Capstone Project & Technical Portfolio in Data Literacy | Practical | Present the completed portfolio of coding artifacts and oral defense of foundational computing concepts in Data Literacy. |
Secondary school completion or relevant initial technical curiosity. English proficiency recommended.
Brookfield School of Computing is an independent private education institution in formation. Academic programmes, entry requirements, fees and awards are subject to institutional review and applicable Swiss legal regulations.