Просмотр кода страницы Introduction to Data Culture 2018-2019

== Materials ==
Your grades are [https://docs.google.com/spreadsheets/d/1-C1NgwMtu755veLafNGvJrjntWNfM_9d7hkxA-GEISs/edit#gid=0 here]<br />

{| class="wikitable"
|-
! № !! Topic !! Slides !! Tutorial & Assignment 
|-
| 1 || Introduction || [https://yadi.sk/i/IXPq8LhtdWBovA Slides1.pdf] || [https://yadi.sk/i/HsSuMQIKzBUixg Practice1.xlsx]
|-
| 2 || Data Characteristics || [https://yadi.sk/i/L2UcugpDyjhK9Q Slides2.pdf] || [https://yadi.sk/i/ZdZGncxIwaT_8A Practice2.xlsx]
|-
| 3 || Conditional Operators || [https://yadi.sk/i/paBMf6_0Ncl-Tw Slides3.pdf] || [https://yadi.sk/i/RaHE4UMCg1w_Bg Practice3.xlsx]
|-
| 4 || Text functions and Pivot tables || [-] || [https://yadi.sk/i/wGAstSLmPrsSbA Practice4.xlsx]
|-
| 5-6 || Time series || [https://yadi.sk/i/5360I2pcQTQarg Slides5-6.pdf] || [https://yadi.sk/i/rZX0H0k1iwHv_A Practice5-6.xlsx]
|-
|-
| 7 || Linear Regression || [https://yadi.sk/i/EiYFaiYJo69cnw Slides7.pdf] || [https://yadi.sk/i/opkUhE-xzMxWlA Practice7.xlsx] 
|-
|}

== Teamwork ==
First two homeworks are considered to be made individually. Later, you can work on the practice assignments in teams, you are free to choose and organise. Teams can contain two or three people.<br /><br />
<br />

== Communication ==
All course materials, assignments, deadlines will be published on [[http://wiki.cs.hse.ru/index.php?title=Introduction_to_Data_Culture_2018-2019&action=edit&redlink=1|this very wiki]].

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

There are Telegram groups [https://t.me/joinchat/HJ_AVw4FyGbVSPuWFaOjnw 1]; [https://t.me/joinchat/HJ_AVxGbuvScrDTNRnUp6w 2&3] for general discussion - please feel free to discuss the course materials there, we’ll create a mailing list.
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 during the seminar.

For example: Practice1_BMOL181_Ivanov
{| class="wikitable"
|-
! Group !! Teacher !! Teaching assistant !! Schedule !! Telegram channel
|-
| BMOL181 || Marina Ananyeva ||  Egor Chernousov || Saturday (3.11, 17.11, 01.12, 15.12) at 12.10-15.00 || [https://www.dropbox.com/sh/qqltptndyj7nzcc/AAAEHVL_C98DtrLy991Is5hXa?dl=0 Here]
|-
| BMOL182 || Marina Ananyeva || Ekaterina Zorina || Saturday (3.11, 17.11, 01.12, 15.12) at 9.00-11.50 || [https://www.dropbox.com/sh/bflpkxbrxsig7x2/AACMGJ7ltyH-1xZmKdxiu7_Na?dl=0 Here]
|-
| BMOL183 || Elena Kantonistova || Ilya Abroskin || Every Friday 9.00-10.30 || [https://t.me/joinchat/Eb8LXw6ecVuR6Xa5IrxjWg Here]
|}
<br />

Links for submitting homeworks for group BMOL181:<br />
[https://t.me/Kuske228 Egor Chernousov (Telegram)]<br />
[mailto:evchernousov@edu.hse.ru Email] evchernousov@edu.hse.ru <br />

Links for submitting homeworks for group BMOL182:<br />
[https://t.me/zorkass Ekaterina Zorina (Telegram)]<br />
[mailto:edzorina@edu.hse.ru  Email] edzorina@edu.hse.ru<br />

Links for submitting homeworks for group BMOL183 <br />
[https://www.dropbox.com/request/nWHdD7CmNEpVfofackhg Practice 1] <br />
[https://www.dropbox.com/request/a3U4dnSSYMnuoejiI1vq Practice 2] <br />
[https://www.dropbox.com/request/gfsn6GCWTIQDdv97xB1j Practice 3] <br />
[https://www.dropbox.com/request/RHsRHhHjTbHxTKSs17aT Practice 4] <br />
[https://www.dropbox.com/request/xNO67fd5LyeDUv2wD5si Practice 5] <br />
[https://www.dropbox.com/request/uOZtpjTHglasN9oIupLl Practice 6] <br />
[https://www.dropbox.com/request/sKMoLrihkpfz3w2jqndM Practice 7] <br />

== Feedback ==
We’ll much appreciate if you help us to make it better by telling your ideas and suggestions. You are free to do it.<br />

== About the course ==
The course is for students of Bachelor’s Programme 'HSE and University of London Parallel Degree Programme in International Relations'.

Your seminar teachers are: Elena Kantonistova ([mailto:elena.kantonistova@yandex.ru email]) and Marina Ananyeva ([mailto:ananyeva.me@gmail.com email]).<br />

== Grading ==
Final Grade = 0.8*Cumulative Grade + 0.2*Exam Grade<br />

Cumulative Grade = 0.7*Homework Grade + 0.3*Class Test Grade + Extra Points <br />
<br />
== Deadlines ==
You must submit each seminar assignment by the beginning of the next one - otherwise you get 0 for it. <br />
<br />
== Attendance ==
<br />
It is better to attend all lectures to be aware of your material. However, 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.<br /><br />

== Force majeure ==
<br />
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.
<br />
<br />
== Fast line ==
<br />
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.<br /><br />
== Hail Mary ==
<br />
If by the end of the course you find yourself with 5 non-zero grades for tests, but 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.<br /><br />

== Cheating and honor ==
<br />
You must abide by the [https://docs.google.com/document/d/1y4JHIdxCriFIrSHO1ZmeWi9Tjx01o4umqnoFxQtVSrI/mobilebasic 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.
<br /><br />
== Rules status ==
<br />
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.<br />
<br />
== MS Excel ==
<br />
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 [https://docs.google.com/document/d/1_49BpcYiCXa8EO7G69lQGXeQRae7x1RrZ2R2-eJJ6io/edit?usp=sharing manual].