# Core CS Courses in the OSSU Curriculum: The Complete 2024 Guide

> Explore the Core CS courses in the OSSU curriculum for 2024. Discover essential programming, math, systems, theory, and more for a solid computer science foundation.

- Repository: [Open Source Society University/computer-science](https://github.com/ossu/computer-science)
- Tags: guide
- Published: 2026-02-24

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**TLDR:** The OSSU (Open Source Society University) Computer Science curriculum organizes its required coursework into **Core CS**, covering the first three years of a typical undergraduate CS degree across eight sub-domains: Core programming, Core math, CS Tools, Core systems, Core theory, Core security, Core applications, and Core ethics, all defined in the repository's [`README.md`](https://github.com/ossu/computer-science/blob/main/README.md).

The [ossu/computer-science](https://github.com/ossu/computer-science) repository provides a comprehensive, open-source path to a computer science education equivalent to a bachelor's degree. The **Core CS courses in the OSSU curriculum** form the academic backbone of this program, structured to mirror the progression of traditional university programs while maintaining modular flexibility for self-paced learners.

## Core CS Structure and Course Requirements

The curriculum divides **Core CS** into eight distinct sub-domains, each containing mandatory courses that build upon specific competencies. According to the [`README.md`](https://github.com/ossu/computer-science/blob/main/README.md) in the repository root, these requirements represent approximately three years of full-time academic study.

### Core Programming

The **Core programming** sub-domain establishes software design fundamentals through five required courses covering functional programming, object-oriented paradigms, and architectural patterns.

Students begin with **[Systematic Program Design](coursepages/spd/README.md)** before advancing to **Class-based Program Design** and **[Programming Languages](https://courses.cs.washington.edu/courses/cse341/19au/#lectures)**. The sequence continues with **[Object-Oriented Design](https://course.ccs.neu.edu/cs3500f19/)** and concludes with **[Software Architecture](https://www.coursera.org/learn/software-architecture)**, bridging theoretical concepts with industry practices like design patterns and type systems.

### Core Math

Mathematical foundations are provided through the **Core math** requirements, ensuring competency in calculus, discrete mathematics, and formal proofs necessary for algorithm analysis.

The curriculum requires completion of MITx's calculus sequence: **[Calculus 1A: Differentiation](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+18.01.1x+2T2019/about)**, **[Calculus 1B: Integration](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+18.01.2x+3T2019/about)**, and **[Calculus 1C: Coordinate Systems & Infinite Series](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+18.01.3x+1T2020/about)**. Learners then complete **[Mathematics for Computer Science](https://openlearninglibrary.mit.edu/courses/course-v1:OCW+6.042J+2T2019/about)**, which covers discrete math, probability, and proof techniques critical for theoretical computer science.

### CS Tools

Before diving into advanced coursework, students complete **CS Tools**, a single-course requirement focusing on development environment mastery.

**[The Missing Semester of Your CS Education](https://missing.csail.mit.edu/)** from MIT covers essential productivity utilities including terminal navigation, vim editing, shell scripting, and version control workflows. This foundational knowledge supports all subsequent **Core CS** work.

### Core Systems

The **Core systems** sub-domain explores hardware-software interfaces, low-level programming, and networked computing through four intensive courses.

The progression starts with **[Build a Modern Computer from First Principles: From Nand to Tetris](https://www.coursera.org/learn/build-a-computer)** and its **[Part II](https://www.coursera.org/learn/nand2tetris2)**, teaching computer architecture from logic gates upward. Students then study **[Operating Systems: Three Easy Pieces](coursepages/ostep/README.md)** (with detailed syllabus in [`coursepages/ostep/README.md`](https://github.com/ossu/computer-science/blob/main/coursepages/ostep/README.md)) before completing **[Computer Networking: a Top-Down Approach](http://gaia.cs.umass.edu/kurose_ross/online_lectures.htm)**.

### Core Theory

Algorithmic thinking and complexity analysis form the **Core theory** requirements, covering the mathematical foundations of computation.

The Stanford sequence **[Algorithms: Design and Analysis, Part 1](https://www.edx.org/learn/algorithms/stanford-university-algorithms-design-and-analysis-part-1)** and **[Part 2](https://www.edx.org/learn/algorithms/stanford-university-algorithms-design-and-analysis-part-2)** introduce sorting algorithms, graph search, dynamic programming, and NP-completeness. These courses directly apply the discrete mathematics and probability concepts from **Core math**.

### Core Security

Modern software development requires security literacy, addressed through three mandatory **Core security** courses.

Students complete **[Cybersecurity Fundamentals](https://www.edx.org/learn/cybersecurity/rochester-institute-of-technology-cybersecurity-fundamentals)** covering CIA triad principles, followed by **[Principles of Secure Coding](https://www.coursera.org/learn/secure-coding-principles)** and **[Identifying Security Vulnerabilities](https://www.coursera.org/learn/identifying-security-vulnerabilities)**. This sequence emphasizes secure design patterns and vulnerability assessment methodologies.

### Core Applications

Practical specialization occurs in **Core applications**, spanning data management, machine learning, graphics, and engineering practices.

Database fundamentals require three Stanford courses: **[Databases: Modeling and Theory](https://www.edx.org/learn/databases/stanford-university-databases-modeling-and-theory)**, **[Databases: Relational Databases and SQL](https://www.edx.org/learn/relational-databases/stanford-university-databases-relational-databases-and-sql)**, and **[Databases: Semistructured Data](https://www.edx.org/learn/relational-databases/stanford-university-databases-semistructured-data)**. Additional requirements include **[Machine Learning](https://www.deeplearning.ai/courses/machine-learning-specialization/)**, **[Computer Graphics](https://www.edx.org/learn/computer-graphics/the-university-of-california-san-diego-computer-graphics)**, and **[Software Engineering: Introduction](https://www.edx.org/learn/software-engineering/university-of-british-columbia-software-engineering-introduction)**.

### Core Ethics

Professional responsibility concludes the **Core CS** requirements through three ethics-focused courses.

Students study **[Ethics, Technology and Engineering](https://www.coursera.org/learn/ethics-technology-engineering)**, **[Introduction to Intellectual Property](https://www.coursera.org/learn/introduction-intellectual-property)**, and **[Data Privacy Fundamentals](https://www.coursera.org/learn/northeastern-data-privacy)**. These address professional ethics, IP law frameworks, and privacy engineering principles essential for responsible technology development.

## Curriculum Architecture and Key Files

The **Core CS** structure follows a deliberate pedagogical progression: foundational tooling precedes programming and mathematics, which enable systems and theory study, followed by security, applications, and finally ethics. This ordering respects academic dependencies—for example, **Core math** concepts are prerequisites for **Core theory** analysis.

According to the repository source code, several files define and support these requirements:

- **[`README.md`](https://github.com/ossu/computer-science/blob/main/README.md)** — Contains the master curriculum table listing all **Core CS** courses and their ordering
- **[`CURRICULAR_GUIDELINES.md`](https://github.com/ossu/computer-science/blob/main/CURRICULAR_GUIDELINES.md)** — Defines the degree-requirement criteria that all **Core CS** courses must satisfy
- **[`coursepages/spd/README.md`](https://github.com/ossu/computer-science/blob/main/coursepages/spd/README.md)** — Detailed syllabus for *Systematic Program Design*, the entry-point programming course
- **[`coursepages/ostep/README.md`](https://github.com/ossu/computer-science/blob/main/coursepages/ostep/README.md)** — Comprehensive resources for *Operating Systems: Three Easy Pieces*
- **[`extras/courses.md`](https://github.com/ossu/computer-science/blob/main/extras/courses.md)** — Catalogs supplemental courses that didn't make the core curriculum but provide additional depth

All courses are free or low-cost open-enrollment offerings, maintained through community contributions documented in [`CONTRIBUTING.md`](https://github.com/ossu/computer-science/blob/main/CONTRIBUTING.md).

## Extracting Core CS Data Programmatically

Developers can programmatically access the **Core CS** course list directly from the repository's [`README.md`](https://github.com/ossu/computer-science/blob/main/README.md) using standard Unix tools or Python scripts.

To display the raw markdown section from the command line:

```bash

# Clone the OSSU CS curriculum repository

git clone https://github.com/ossu/computer-science.git
cd computer-science

# Show the Core CS section (Markdown filtered)

grep -A20 -i "## Core CS" README.md

```

For automated extraction of course titles using Python:

```python

# Minimal Python script to extract core-course titles from the README

import pathlib, re

readme = pathlib.Path("README.md").read_text()
core_section = re.search(r"## Core CS(.+?)##", readme, re.S).group(1)

# Find all markdown links inside the Core CS block

courses = re.findall(r"\[([^\]]+)\]\([^\)]+\)", core_section)
for c in courses:
    print(c)

```

These scripts parse the canonical curriculum definition in [`README.md`](https://github.com/ossu/computer-science/blob/main/README.md), ensuring extracted data reflects the current `master` branch state.

## Summary

- **Core CS** represents the mandatory coursework equivalent to the first three years of a bachelor's degree in computer science within the OSSU curriculum.
- The curriculum organizes **Core CS** into eight sub-domains: Core programming, Core math, CS Tools, Core systems, Core theory, Core security, Core applications, and Core ethics.
- Course sequencing follows pedagogical dependencies, with mathematics preceding theory and programming fundamentals enabling systems study.
- All course requirements are defined in the repository's **[`README.md`](https://github.com/ossu/computer-science/blob/main/README.md)**, with detailed syllabi hosted in subdirectories like `coursepages/spd/` and `coursepages/ostep/`.
- The 24+ required courses cover everything from Nand to Tetris computer architecture to machine learning and professional ethics.

## Frequently Asked Questions

### How long does it take to complete all Core CS courses in the OSSU curriculum?

Completion time varies by learner availability and prior experience, but the **Core CS** curriculum generally requires 18 to 24 months of consistent part-time study. The eight sub-domains contain over 24 individual courses, with substantial programming projects in systems and applications tracks. Students typically dedicate 15-20 hours weekly to maintain steady progress through the mathematics and programming fundamentals.

### Are the Core CS courses in the OSSU curriculum completely free?

Yes, all **Core CS** courses are free to audit or available at minimal cost through platforms like edX, Coursera, and MIT Open Learning Library. The OSSU curriculum specifically selects open-enrollment courses with free content access, though some platforms charge for certificates of completion. The repository maintains links to the no-cost versions in [`README.md`](https://github.com/ossu/computer-science/blob/main/README.md).

### What is the relationship between Core CS and the courses listed in extras/courses.md?

While **Core CS** courses in the OSSU curriculum are mandatory requirements equivalent to undergraduate degree standards, [`extras/courses.md`](https://github.com/ossu/computer-science/blob/main/extras/courses.md) catalogs supplemental courses that provide additional depth or alternative explanations but did not meet the specific curricular criteria defined in [`CURRICULAR_GUIDELINES.md`](https://github.com/ossu/computer-science/blob/main/CURRICULAR_GUIDELINES.md). Learners often use these extras for review or to explore topics like specialized programming languages after completing the core requirements.

### Can experienced developers skip the CS Tools section of Core CS?

Although experienced developers may possess the skills taught in **CS Tools** (The Missing Semester), the OSSU curriculum lists it as a **Core CS** requirement to ensure standardized baseline knowledge across all learners. However, the self-paced nature of the curriculum allows learners to assess their competency against the topics—terminal navigation, vim, shell scripting, and version control—before proceeding to **Core programming** coursework.