Introduction to Data Culture

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Materials

Your grades are here.

Тема лекции лекция семинар Errata Bonus tasks worth
1 Введение Lecture1.pdf Practice1.xlsx Practice1 Erratum 10
2 --- --- Practice2.xlsx Practice2 Errartum 10
3 Интернет и Этика [1] Practice3.xlsx Practice3 Errartum 5 + 15 (competition)
4 --- --- Practice4.xlsx 10
5 TBA TAB in-class assessment TBA

Communication

All the course materials, assignments, deadlines will be published on this very wiki.

All the practical announcements concerning the whole course (such as lecture cancellation) will appear in the Telegram channel.

There is a Telegram group for general discussion - please feel free to discuss the course materials there, we’ll create a mailing list.

Please send the assignments and questions to your teaching assistant.

The preferred way to contact the us is by email.

Letter subject format (We'd appreciate a lot if you stick to it, as it makes managing correspondence a lot easier):

  • Question - GroupNumber - Surname Name
  • Practice {number of the seminar} - GroupNumber - Surname Name

Also, please name your tasks in this format: Practice#PracticeNumber#_#Group number#_#Team number#_#Names of participants#, where the Team number is the number of the team in which you work on the seminar.

For example: Practice1_BMOL171_3_IvanovPetrovSidorov

Group Teacher Teaching assistant Schedule Telegram channel
БМОЛ171 Elena Kantonistova, email Ilya Abroskin, email Thursday, 10.30, 422 here
БМОЛ172 Elena Kantonistova, email Anastasiya Maksimovskaya, email, telegram Thursday, 9.00, 422 here
БМОЛ173 Nikita Kazeev,email Ivan Buyukliyski, email, telegram Thursday, 12.10, 422 here
БМОЛ174 Elena Kantonistova, email Alexander Stolnikov, email Thursday, 13.40, 422 here

Feedback

This is the first time this course is taught - we’ll much appreciate if you help us make it better by telling your ideas and suggestions. If you prefer anonymous feedback, there is a form for it.

О курсе

Курс читается для студентов 1-го года обучения бакалаврской программы «Программа двух дипломов НИУ ВШЭ и Лондонского университета "Международные отношения"»

Лекции читает Деркач Денис

Семинары ведут: Кантонистова Елена Казеев Никита

Rules

Grading

Except from the general course description:

Final assessment = 0.8*Ongoing Assessment + 0.2*Examination Assessment,

Ongoing Assessment = 0.3*Tests + 0.5*Homework + 0.2*Midterm Examination

Tests - grade you get for the in-class seminars. During each seminar there will be an assignment worth 10 points (with possible bonuses).

Tests = min(10, sum_of_your_grades_for_seminars/number_of_seminars)

The two homework assignments will be announced separately. Those will be mini-projects requiring a bit of thinking and creativity.

Deadlines

You must submit each seminar assignment by the beginning of the next one - otherwise you get 0 for it.

Homeworks will have deadlines when announced.

Attendance

You can attend as frequently as you want - as far as we are concerned. There are two caveats though:

  • You are responsible for catching up with the material and timely submission of all the assignments. We reserve the right to respond “RTFM” to questions from people who missed the corresponding class for no good reason.
  • HSE bureaucracy has asked us to submit the roll-call of each seminar - they might apply some punishment for truancy.

Force majeure

We use the standard HSE rules to determine what counts as a force majeure - illness and stuff. If you encounter one, please email the practice teacher ASAP and then provide the proof documents to the student's office (учебный офис). Your deadlines will be extended by the duration of the illness, and help with the missed material will be offered. Also since you won't be working in a team, you need to complete only half of the obligatory tasks to get a 10, and half of the bonus tasks to get the full grade for the bonus tasks.

Fast lane

If you find yourself offended by a proposition to do data analysis in Excel because you are a Tensorflow contributor, or for any other reason you already know everything this course has to offer - please come forward. Prove yourself a competent data scientist (something line achieving a reasonable place on a Kaggle competition, and passing an oral examination - the precise way will be negotiated and publicized). You’ll get a full grade on Ongoing Assessment and a free pass on all the ongoing assignments in exchange for attending the practical lessons in the role of teaching assistant - helping you classmates and answering their questions.

Hail Mary

If by the end of the course you find yourself with not enough Ongoing Assessment credits to earn a passing grade, there will be a way to make it up with a few extra assignments, for up to the lowest “Satisfactory”. There will be deadlines, they’ll be announced. Please don’t let the situation to deteriorate to that.

Retaking the final exam is governed by the standard HSE rules.

Cheating and honor

You must abide by the Honor Code.

Please don’t cheat - the rumor has it HSE has quite severe penalties.

To avoid being accused of plagiarism in “grey cases” please disclose with whom and how you have collaborated on each assignment outside of the assigned group. This way the worst thing that can happen to you after a good faith mistake is being asked to do a different variant of the task in question, with no disciplinary penalty and no notification of the HSE bureaucracy.

Rules status

We did our best to lay out what’s expected from students in the Data Culture course and don’t expect to make substantial alteration to this document. However, should a loophole arise and be abused, we reserve the right to alter the rules. This of course will be announced on the course channel.

MS Excel

The official and supported version of Microsoft Excel for this course is 2016. It is readily available to HSE students - just login (and possibly register with your @edu.hse.ru email) on the website. In case you have trouble downloading, there is a manual.