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CS 72803 credit hours

Network Science

Mathematical and computational analysis of complex networks: structure, dynamics, and processes on networks.

Machine Learning · electivegraphsmathPython

Distributions

Difficulty
3.6of 5
n = 9
0
0
5
3
1
1
2
3
4
5
Weekly workload
14.0hrs/wk
n = 9
0
1
3
5
0
0
0
0
<5
5–9
10–14
15–19
20–24
25–29
30–34
35+
Overall rating
4.2of 5
n = 9
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0
1
5
3
1★
2★
3★
4★
5★

Logistics

Terms offered
Fall
Spring
Summer
Prerequisites
  • Probability
Counts toward
  • Machine Learningelective

Reviews (9)

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9 of 9
  1. 5 / 5
    Difficulty3/5Workload18 hr/wkRecommendYes

    Took this in Summer 2023. Workload averaged ~18 hrs/wk. Difficulty felt fair. Assignments build on each other.

  2. 5 / 5
    Difficulty5/5Workload11 hr/wkRecommendYes

    brutal pace, light hours weekly. Coming in I had an undergrad CS background. Glad I stuck with it.

  3. 4 / 5
    Difficulty4/5Workload16 hr/wkRecommendYes

    If you have industry experience in backend, this is approachable. Otherwise plan for ~16 hrs/wk and a few late nights.

  4. 4 / 5
    Difficulty3/5Workload6 hr/wkRecommendYes

    Took this in Fall 2023. Workload averaged ~6 hrs/wk. Difficulty felt fair. Instructors engage in forums.

  5. 4 / 5
    Difficulty4/5Workload16 hr/wkRecommendYes

    Would I take it again? Yes. The course rewards consistent weekly effort.

  6. 5 / 5
    Difficulty3/5Workload18 hr/wkRecommendYes

    Project-driven course. Most of the 18 hrs/wk go to assignments rather than lectures.

  7. 4 / 5
    Difficulty3/5Workload17 hr/wkRecommendYes

    fair pace, moderate hours weekly. Coming in I had an undergrad CS background. Glad I stuck with it.

  8. 4 / 5
    Difficulty3/5Workload10 hr/wkRecommendYes

    If you have a math-heavy background, this is approachable. Otherwise plan for ~10 hrs/wk and a few late nights.

  9. 3 / 5
    Difficulty4/5Workload14 hr/wkRecommendYes

    Project-driven course. Most of the 14 hrs/wk go to assignments rather than lectures.