Question 1

Is IE3013 hard at UMN?

Accepted Answer

Based on 5 student reviews, IE3013 has a high challenge level (72/100). Grade accessibility is very high (100/100), meaning most students earn A or B grades.

Question 2

How many hours per week is IE3013?

Accepted Answer

Students report a high time investment (72/100). Expect to spend approximately 10-15 hours per week on coursework, including lectures, assignments, and studying.

Question 3

What is the grading like in IE3013?

Accepted Answer

Grade accessibility for IE3013 is rated 100/100. The course is assessed primarily through mixed methods.

Question 4

Is attendance mandatory for IE3013?

Accepted Answer

Attendance importance is rated 0/100. Attendance is generally not mandatory, though going to class is always beneficial.

Question 5

What type of assignments does IE3013 have?

Accepted Answer

IE3013 is classified as "Mixed" based on student feedback. Common themes from student reviews include: clear grading criteria, lots of homework, lecture heavy, tough grader. The challenge level is high (72/100).

Question 6

Would students recommend IE3013?

Accepted Answer

80% of students would recommend IE3013. Student satisfaction is rated 84/100. This course is generally well-regarded by students who have taken it.

IE3013: Optimization for Machine Learning

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