Sign-Up Survey | GIST DataEng Spring 2024

Welcome to the 2024 Spring - GIST Data Engineering (AI5308/AI4005). This form helps us get to know you better so that we can use the information to improve the course design. (Due: Mar 7)
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Name in English? *
Name in Korean (if you have one)
GIST Student Number *
Preferred email address (Provide one you check frequently.)
 *
Your Major
 *
I am confident in programming with at least one of the following languages: Python, C, C++, Java, or Objective C.
 *
No, I am not
Yes, I am
I am confident in Machine Learning Programming:
(e.g., PyTorch, XGBoost, pandas, numpy, Kaggle)
 *
No, I am not
Yes, I am
I am confident in using HTML/CSS.
 *
No, I am not
Yes, I am
I am confident in using programming with Javascript or React
 *
No, I am not
Yes, I am
I am confident in mobile app development.
No, I am not
Yes, I am
Clear selection
I am confident in collaborative software development using Git.
 *
No, I am not
Yes, I am
I am confident in presenting my work (in English).
 *
No, I am not
Yes, I am
I am confident in writing my work (in English). *
No, I am not
Yes, I am
Have you ever participated in developing club or Hackathon?
No, I haven't
Yes, I have
Clear selection
Have you ever participated in machine learning competition? 
No, I haven't
Yes, I have
Clear selection
Do you have a laptop or a desktop computer? *
Note that it's not mandatory to own a computer / laptop to take this course. But it's recommended to have one for in-class activities and assignments.
 *
Do you have access to a mobile phone or a tablet? (or any other device with a screen and an internet connection)
 *
What is the primary reason you're interested in taking this course?
 *
What have you heard about this course?
What is one thing you're expecting to learn from this course?
 *
What is one thing that makes you worried about this course?
 *
Will you take this course?
(If you will take this course, please register Ed discussion and Gradescope, see https://sundong.kim/courses/dataeng24sp/) *
We will have special seminars on the following schedule. Feel free to attend those. (not mandatory)
- March 22 (Fri) 10:30-12:00
  (Speaker 1: Xing Xie, Microsoft, Societal AI: Tackling AI Challenges with Social Science Insights)
  (Speaker 2: Fangzhao Wu, Microsoft, Towards Responsible Large Language Models)
- March 22 (Fri) 14:00-15:30 
  (Speaker 1: Meeyoung Cha, IBS/KAIST, Making Discoveries for Humanity and Society with Data Science )
  (Speaker 2: Seong-Eon Lee, IBS/KAIST, Generative AI is not explainable AI)
- Mar 29 (Thu) 16:00-17:30
  (Speaker: Hayan Choi - V2V - 스타트업에서 머신러닝의 활용 시도에 대한 케이스 스터디)

Location: AI Graduate School 2F - TED Hall
(* Mark your Calendar)
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