OMSCS Open Courseware

Original Article ↗ Hacker News Discussion ↗

Workload, Time Management, and Family Life

  • Many posters with jobs and kids say OMSCS is doable only at 1 course/semester, and even then it consumes most free time.
  • Typical reported loads range from ~8–10 hours/week for easier classes to 25–30+ hours for harder ones (Graduate Algorithms, ML, some systems courses).
  • Some projects, especially in Distributed Computing (Paxos + sharded KV store), were described as 60–80‑hour slogs, with lost sleep and sacrificed weekends.
  • Several people finished with young kids thanks to remote work and supportive partners, but multiple commenters said they wouldn’t do it again due to the health and lifestyle impact.

What You Get Beyond Open Courseware

  • Repeated emphasis that the main value is not lectures but:
    • challenging assignments and auto‑grading,
    • TA feedback on code and written reports,
    • peer review,
    • deadlines and exams as a forcing function,
    • community via Ed/Discord/Slack,
    • access to libraries and software.
  • Open courseware is seen as a useful “try before you buy,” but some note other universities publish more complete open materials (with assignments and labs) if you don’t care about credit.

Program Quality and Specific Courses

  • Overall program is widely described as rigorous, with a low completion rate despite a relatively high acceptance rate.
  • Some courses are called out as excellent: Graduate Algorithms, Advanced OS, HPC, ML, Video Game Design, GIOS, DSI (database implementation).
  • The legacy database course is criticized as too shallow; the new implementation-focused DB course is defended as significantly more rigorous and aligned with on‑campus content.

Degree Value and LLM Era Debate

  • One line of argument: online degrees are losing signaling value in a world of LLM‑assisted coding; a motivated person could self‑study with a textbook and an LLM.
  • Counterarguments:
    • OMSCS diploma is identical to the in‑person MSCS and is respected in industry.
    • Exams are hard enough that “winging it with LLMs” on assignments won’t get you through.
    • Several posters report substantial career boosts (e.g., moving into ML roles at top companies).

Admissions and Practicalities

  • Letters of recommendation are generally seen as a formality; professional references from managers are common.
  • GRE often not required; CS undergrad with decent grades tends to make admission straightforward.
  • Tools like OMSHub/OMScentral help with course selection; scripts with ffmpeg help merge the many 2‑minute lecture clips.
  • Question about truly self‑paced or doubled-speed completion remains unanswered/unclear.