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Introduction to Machine Learning - Get to know you better questionnaire
Please take your time and fill this questionnaire. It will help us know you and your needs better towards the upcoming semester. Feel free to use the open text box below to give us any further course-related details.
* Indicates required question
Email address
*
Your answer
What semester are you in?
*
3
4
5
6 and above
MSc student
PhD student
Not a student (free listener)
Other:
Which is your main faculty?
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Computer science
Electrical engineering
Industrial engineering
Mechanical engineering
Math
Physics
Other:
How do you currently plan to watch the lectures?
*
Your answer is not obligating, but we need to prepare.
Physically attend the hybrid class (Tuesdays at 12:30-14:30, Taub 2)
Virtually attend the hybrid class on Zoom (Tuesdays at 12:30-14:30)
Watch recordings on Panopto
Not yet decided
Other:
How do you currently plan to watch the tutorials?
*
Your answer is not obligating, but we need to prepare.
Physically attend Itay's hybrid class (Tuesdays at 14:30-15:30, Taub 5)
Virtually attend Itay's hybrid class on Zoom (Tuesdays at 14:30-15:30)
Virtually attend Amir's class on Zoom (Wednesdays at 15:30-16:30)
Virtually attend Guy's class on Zoom (Mondays at 10:30-11:30)
Watch recordings on Panopto
Not yet decided
Other:
When did you take an introductory course in probability?
*
Last semester
2-3 semesters ago
4 semesters ago or before that
Other
When did you take a course in numerical algorithms (or numerical analysis)?
*
Last semester
2-3 semesters ago
4 semesters ago or before that
Did not take such a course
Other
What other related courses you took?
Statistics
Deep learning
Optimization
Computer vision
Image/signal processing
Natural language processing
Artificial intelligence
How would you rate your Python skills?
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What is Python?
0
1
2
3
4
5
Excellent skills
Do you have any children?
We need to know if you are entitled to parent adjustments.
Yes
No
Choose not to disclose
Clear selection
Here is the place to bring us your special needs, requests, or course-related ideas.
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