# Time Commitment for Each Programming Language Course in the Open Source CS Degree > Discover the time commitment for each programming language course in the ForrestKnight/open-source-cs degree. Expect 12-80 hours per course based on your study pace. - Repository: [Forrest Knight/open-source-cs](https://github.com/ForrestKnight/open-source-cs) - Tags: getting-started - Published: 2026-05-01 --- **The nine programming language courses in the ForrestKnight/open-source-cs repository require between 12 and 80 hours each, depending on the specific course and your weekly study pace.** The **Open Source CS** curriculum organized by Forrest Knight includes a dedicated Programming section featuring nine language-focused courses. Understanding the exact time commitment for each programming language course helps you plan realistic weekly schedules and estimate degree completion timelines. All duration data is extracted directly from the [`README.md`](https://github.com/ForrestKnight/open-source-cs/blob/main/README.md) file in the repository root. ## How to Calculate Total Course Hours Each course listing in [`README.md`](https://github.com/ForrestKnight/open-source-cs/blob/main/README.md) provides two critical metrics: **duration in weeks** and **weekly effort in hours**. To determine the total time commitment, multiply the number of weeks by the weekly hour range. For example, a course running 4 weeks at 4–8 hours per week requires **16–32 hours** total. This calculation method applies consistently across all nine entries, allowing you to budget time based on whether you study at the minimum or maximum recommended pace. ## Java Programming Track The curriculum includes six sequential Java courses offered through Duke University. These vary in intensity, with capstone projects requiring less time than foundational data structure courses. - **Java Programming: Solving Problems with Software**: 4 weeks at 4–8 hours/week = **16–32 hours** total (line 15) - **Java Programming: Arrays, Lists, and Structured Data**: 4 weeks at 4–8 hours/week = **16–32 hours** total (line 16) - **Object Oriented Programming in Java**: 6 weeks at 4–6 hours/week = **24–36 hours** total (line 17) - **Data Structures and Performance**: 6 weeks at 6–10 hours/week = **36–60 hours** total (line 18) - **Java Programming: Principles of Software Design**: 4 weeks at 4–8 hours/week = **16–32 hours** total (line 19) - **Java Programming: Build a Recommendation System**: 4 weeks at 3–6 hours/week = **12–24 hours** total (line 20) The **Data Structures and Performance** course demands the highest commitment in this track at up to 60 hours, while the final **Recommendation System** capstone requires the least (12–24 hours). ## Programming Languages Specialization The University of Washington's Programming Languages trilogy focuses on functional programming concepts and requires significantly higher weekly intensity than the Java track. - **Programming Languages, Part A**: 5 weeks at 8–16 hours/week = **40–80 hours** total (line 21) - **Programming Languages, Part B**: 3 weeks at 8–16 hours/week = **24–48 hours** total (line 22) - **Programming Languages, Part C**: 3 weeks at 8–16 hours/week = **24–48 hours** total (line 23) These courses represent the heaviest time investment in the entire programming section, with **Part A** potentially requiring up to 80 hours of study time. ## Planning Your Study Schedule When mapping your progression through the open-source CS degree, consider the **cumulative load** of sequential courses. The six Java courses collectively require **120–204 hours**, while the three Programming Languages courses demand **88–176 hours**. If studying part-time at 10 hours per week, the Java track takes approximately 3–5 months to complete, whereas the Programming Languages specialization requires 2–4 months despite having fewer courses due to the higher hourly intensity per week. ## Summary - The **minimum** time commitment for any programming language course is **12 hours** (Java Recommendation System). - The **maximum** is **80 hours** (Programming Languages Part A). - Java courses range from **12–60 hours** depending on complexity, with data structures requiring the most time. - Programming Languages courses require **8–16 hours per week**, making them roughly twice as intensive as introductory Java courses. - All duration data originates from specific line references in [`README.md`](https://github.com/ForrestKnight/open-source-cs/blob/main/README.md) (lines 15–23). ## Frequently Asked Questions ### How many total hours are required for all programming language courses combined? Completing all nine courses requires approximately **208–380 hours** of study time. This combines the Java track (120–204 hours) with the Programming Languages specialization (88–176 hours). At a consistent 10 hours per week study pace, expect to spend 5–9 months on this section alone. ### Which programming language course takes the longest to complete? **Programming Languages, Part A** requires the longest time commitment at **40–80 hours** over 5 weeks. According to line 21 of [`README.md`](https://github.com/ForrestKnight/open-source-cs/blob/main/README.md), this course demands 8–16 hours per week, making it significantly more intensive than the Java foundation courses. ### Can I complete the Java courses faster than the estimated duration? Yes, the time estimates assume you follow the suggested weekly effort ranges. If you dedicate more hours per week than the maximum listed (e.g., studying 12 hours/week for a course rated 4–8 hours), you can finish in fewer calendar weeks. However, the **total hours required** (12–80 hours per course) remains constant regardless of schedule compression. ### Where does the time commitment data originate in the repository? All figures come from the **Programming** section table in [`README.md`](https://github.com/ForrestKnight/open-source-cs/blob/main/README.md) at the repository root. Each course entry lists specific week counts and hourly ranges, allowing the calculation of total time by multiplying these values as demonstrated in the curriculum documentation.