How Long Does It Take to Complete the Open-Source CS Degree?

Completing the entire Open-Source Computer Science curriculum takes approximately 182 weeks of full-time study, which translates to roughly 3 years and 6 months.

The ForrestKnight/open-source-cs repository curates free university-level courses equivalent to a complete bachelor's degree in computer science. According to the README.md file, each course entry includes a duration in weeks, enabling learners to calculate the total time investment required to finish the entire program.

Duration Breakdown by Subject Area

The 182-week total spans seven core competencies, from introductory programming to advanced theory. Below is the detailed breakdown as listed in the repository's master branch.

Computer Science Basics (10 Weeks)

The curriculum begins with Intro to Computer Science, a 10-week foundational course that covers basic programming concepts and computational thinking (source).

Programming (39 Weeks)

The programming sequence emphasizes Java and programming language theory across nine distinct courses:

• Java Programming: Solving Problems with Software – 4 weeks (L15)
• Java Programming: Arrays, Lists, and Structured Data – 4 weeks (L16)
• Object Oriented Programming in Java – 6 weeks (L17)
• Data Structures and Performance – 6 weeks (L18)
• Java Programming: Principles of Software Design – 4 weeks (L19)
• Java Programming: Build a Recommendation System – 4 weeks (L20)
• Programming Languages, Part A – 5 weeks (L21)
• Programming Languages, Part B – 3 weeks (L22)
• Programming Languages, Part C – 3 weeks (L23)

Mathematics (63 Weeks)

Mathematics requirements consume the largest time block, totaling over one year of study:

• Calculus 1A: Differentiation – 12 weeks (L29)
• Calculus 1B: Integration – 15 weeks (L30)
• Calculus 1C: Coordinate Systems & Infinite Series – 8 weeks (L31)
• Linear Algebra – Foundations to Frontiers – 15 weeks (L32)
• Introduction to Probability and Data – 5 weeks (L33)
• Intro to Statistics – 8 weeks (L34)

Computer Systems (12 Weeks)

Systems courses focus on hardware implementation:

• Build a Modern Computer: From Nand to Tetris – 6 weeks (L41)
• Build a Modern Computer: From Nand to Tetris II – 6 weeks (L42)

Theory (22 Weeks)

Algorithmic theory and computational models require:

• Computer Science: Algorithms, Theory, and Machines – 10 weeks (L50)
• Algorithms, Part I – 6 weeks (L51)
• Algorithms, Part II – 6 weeks (L52)

Applications (31 Weeks)

Practical implementation courses include:

• Software Engineering: Introduction – 6 weeks (L59)
• Machine Learning – 11 weeks (L60)
• Database Management Essentials – 7 weeks (L61)
• Cryptography I – 7 weeks (L62)

Unix Tools (5 Weeks)

Command-line proficiency requirements:

• Linux Command Line Basics – 1 week (L68)
• The Unix Workbench – 4 weeks (L69)

Calculating Completion Time Programmatically

You can verify the total duration using the course data from README.md. The following Python script sums the weeks and converts them to years:

courses = [
    10,  # Intro to Computer Science

    4, 4, 6, 6, 4, 4,  # Java sequence

    5, 3, 3,  # Programming Languages A, B, C

    12, 15, 8, 15, 5, 8,  # Math

    6, 6,  # Systems

    10, 6, 6,  # Theory

    6, 11, 7, 7,  # Applications

    1, 4,  # Unix

]

total_weeks = sum(courses)
years, remaining_weeks = divmod(total_weeks, 52)

print(f"Total duration: {total_weeks} weeks")
print(f"Equivalent to: {years} years and {remaining_weeks} weeks")

# Output: Total duration: 182 weeks

#         Equivalent to: 3 years and 26 weeks

Variables Affecting Time to Completion

While 182 weeks represents the estimated full-time commitment, individual completion times vary based on study intensity and prior knowledge.

• Full-time vs. part-time: Studying 20 hours weekly instead of 40 could double the timeline to approximately 7 years.
• Prerequisite knowledge: Students with prior calculus or programming experience can skip remedial work or accelerate through familiar material.
• Course availability: While the repository links to self-paced MOOCs, some platforms operate on fixed schedules that may delay progression.

Summary

• The Open-Source CS degree requires 182 weeks of structured learning according to the repository's README.md.
• At a full-time pace of 52 weeks per year, completion takes approximately 3.5 years.
• Mathematics courses constitute the largest time investment at 63 weeks (nearly 35% of the total curriculum).
• The curriculum includes 27 distinct courses across seven subject domains.
• Modifications to the master branch may adjust these figures as courses are added or removed.

Frequently Asked Questions

How long does it take to finish the open-source CS degree part-time?

Part-time learners studying 10–20 hours weekly typically require 6 to 8 years to complete all 182 weeks of coursework. The mathematics sequence alone (63 weeks) takes approximately 15 months at a half-time pace.

Is the 182-week estimate accurate for everyone?

The estimate reflects the sum of official course durations listed in README.md, but actual completion varies by individual aptitude and prior experience. Some learners may require additional time for the 15-week Calculus 1B or 15-week Linear Algebra courses, while experienced programmers might complete the 39-week programming section faster than scheduled.

What is the most time-consuming section of the open-source CS degree?

The Mathematics section requires 63 weeks, making it the longest component—longer than Programming (39 weeks) and Applications (31 weeks) combined. Specifically, Calculus 1B: Integration (15 weeks) and Linear Algebra – Foundations to Frontiers (15 weeks) are the single longest courses in the entire curriculum.

Can I complete the open-source CS degree faster than 3.5 years?

Accelerated completion is possible if you have substantial prior knowledge or study more than full-time hours. However, the repository structure assumes sequential completion of prerequisites; you cannot compress the 11-week Machine Learning course or 6-week Nand to Tetris projects below their designed durations without sacrificing comprehension of the material.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}