Wiki - Факультет компьютерных наук - Вклад [ru]

Introduction to Data Culture 2019-2020

2019-10-29T20:34:59Z

Chernik: Добавлены контакты

==Materials==

Your grades are [https://docs.google.com/spreadsheets/d/1OtJR4Vhk8FkFHXQhJqp9VLfa9zsQ-TXGFFiF8ATmMAo/edit?usp=sharing here]
{| class="wikitable"
|-
! № !! Topic !! Slides !! Tutorial and Assignment !! Additional Materials
|-
| style="background:#eaecf0;" | '''1''' || Introduction to Data Science || https://yadi.sk/i/0f3Le1LmWT2kbw || https://yadi.sk/i/XWW37z-PH2EXug || https://bit.ly/367Ej8p
|-
| style="background:#eaecf0;" | '''2''' || || || ||
|-
| style="background:#eaecf0;" | '''3''' || || || ||
|-
| style="background:#eaecf0;" | '''4''' || || || ||
|-
| style="background:#eaecf0;" | '''5-6''' || || || ||
|-
| style="background:#eaecf0;" | '''7''' || || || ||
|}

==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.

==Communication==

All course materials, assignments, deadlines will be published on [http://wiki.cs.hse.ru/Introduction_to_Data_Culture_2019-2020 very wiki].

All practical announcements concerning the whole course (such as lecture cancellation) will appear on the Telegram channel https://t.me/joinchat/Du3HEUStPxVGVwnEvkzokw

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
|-
| style="background:#eaecf0;" | '''BMOL191''' || Marina Ananyeva [mailto:ananyeva.me@gmail.com Email] [https://t.me/ananyevame Telegram] || Egor Chernousov || Thursday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL192''' || Marina Ananyeva [mailto:ananyeva.me@gmail.com Email] [https://t.me/ananyevame Telegram] || Valeriya Rusina || Thursday 10:30 - 11:50
|-
| style="background:#eaecf0;" | '''BMOL193''' || Marina Ananyeva [mailto:ananyeva.me@gmail.com Email] [https://t.me/ananyevame Telegram]|| Liana Gainutdinova || Monday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL194''' || Marina Ananyeva [mailto:ananyeva.me@gmail.com Email] [https://t.me/ananyevame Telegram]|| Polina Semenova || Tuesday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL195''' || Ilya Abroskin || Andrey Chernikov [mailto:amchernikov@edu.hse.ru Email] [https://t.me/chernik28 Telegram] || Monday 13:40-15:00
|-
| style="background:#eaecf0;" | '''BMOL196''' || Ilya Abroskin || Andrey Chernikov [mailto:amchernikov@edu.hse.ru Email] [https://t.me/chernik28 Telegram] || Monday 12:10-13:30
|-
| style="background:#eaecf0;" | '''BMOL197''' || Elena Kantonistova || Mikhail Belkin || Monday 10:30-11:50
|-
| style="background:#eaecf0;" | '''BMOL198''' || Elena Kantonistova || Mikhail Belkin || Monday 09:00-10:20
|}

Links for submitting homeworks for group BMOL191:

Links for submitting homeworks for group BMOL192:

Links for submitting homeworks for group BMOL193:

[https://www.dropbox.com/request/JkVG5PXDnyJzRQ7VGp2o Practice 1]

Links for submitting homeworks for group BMOL194:

Links for submitting homeworks for group BMOL195: [https://www.dropbox.com/request/55ZgClZ7yGo2nNKIsEnS Practice 1]

Links for submitting homeworks for group BMOL196: [https://www.dropbox.com/request/JQlEain1m9c9tKXCLuZy Practice 1]

Links for submitting homeworks for group BMOL197:

Links for submitting homeworks for group BMOL198:

==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!

Anonymous feedback form: [https://bit.ly/36fnkB3 click_here]

==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 and Marina Ananyeva.

==Grading==

Final Grade = 0.5*(Homework + Extra Points*) + 0.2*Control Work + 0.3*Examination Assessment

*In the beginning of each seminar students are asked to perform tests to check knowledge based on the materials of previous seminars. Each 100% correctly completed test provides the student with extra points that go towards ongoing assessment.

==Deadlines==

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

==Attendance==

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.

==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 line==

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 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.

==Cheating and honor==

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.

==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 [https://docs.google.com/document/d/1_49BpcYiCXa8EO7G69lQGXeQRae7x1RrZ2R2-eJJ6io manual].

Introduction to Data Culture 2019-2020

2019-10-29T14:00:35Z

Chernik: Добавление названий в ссылки

==Materials==

Your grades are [https://docs.google.com/spreadsheets/d/1OtJR4Vhk8FkFHXQhJqp9VLfa9zsQ-TXGFFiF8ATmMAo/edit?usp=sharing here]
{| class="wikitable"
|-
! № !! Topic !! Slides !! Tutorial and Assignment !! Additional Materials
|-
| style="background:#eaecf0;" | '''1''' || Introduction to Data Science || https://yadi.sk/i/0f3Le1LmWT2kbw || https://yadi.sk/i/XWW37z-PH2EXug || https://bit.ly/367Ej8p
|-
| style="background:#eaecf0;" | '''2''' || || || ||
|-
| style="background:#eaecf0;" | '''3''' || || || ||
|-
| style="background:#eaecf0;" | '''4''' || || || ||
|-
| style="background:#eaecf0;" | '''5-6''' || || || ||
|-
| style="background:#eaecf0;" | '''7''' || || || ||
|}

==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.

==Communication==

All course materials, assignments, deadlines will be published on [[wiki.cs.hse.ru/Introduction_to_Data_Culture_2019-2020|[very wiki]]].

All practical announcements concerning the whole course (such as lecture cancellation) will appear on the Telegram channel https://t.me/joinchat/Du3HEUStPxVGVwnEvkzokw

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
|-
| style="background:#eaecf0;" | '''BMOL191''' || Marina Ananyeva || Egor Chernousov || Monday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL192''' || Marina Ananyeva || Valeriya Rusina || Tuesday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL193''' || Marina Ananyeva || Liana Galnutdinova || Thursday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL194''' || Marina Ananyeva || Polina Semenova || Thursday 10:30 - 11:50
|-
| style="background:#eaecf0;" | '''BMOL195''' || Ilya Abroskin || Andrey Chernikov || Monday 13:40-15:00
|-
| style="background:#eaecf0;" | '''BMOL196''' || Ilya Abroskin || Andrey Chernikov || Monday 12:10-13:30
|-
| style="background:#eaecf0;" | '''BMOL197''' || Elena Kantonistova || Mikhail Belkin || Monday 10:30-11:50
|-
| style="background:#eaecf0;" | '''BMOL198''' || Elena Kantonistova || Mikhail Belkin || Monday 09:00-10:20
|}

Links for submitting homeworks for group BMOL191:

Links for submitting homeworks for group BMOL192:

Links for submitting homeworks for group BMOL193:

[https://www.dropbox.com/request/JkVG5PXDnyJzRQ7VGp2o Practice 1]

Links for submitting homeworks for group BMOL194:

Links for submitting homeworks for group BMOL195: [https://www.dropbox.com/request/55ZgClZ7yGo2nNKIsEnS Practice 1]

Links for submitting homeworks for group BMOL196: [https://www.dropbox.com/request/JQlEain1m9c9tKXCLuZy Practice 1]

Links for submitting homeworks for group BMOL197:

Links for submitting homeworks for group BMOL198:

==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.

==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 and Marina Ananyeva.

==Grading==

Final Grade = 0.5*(Homework + Extra Points*) + 0.2*Control Work + 0.3*Examination Assessment

*In the beginning of each seminar students are asked to perform tests to check knowledge based on the materials of previous seminars. Each 100% correctly completed test provides the student with extra points that go towards ongoing assessment.

==Deadlines==

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

==Attendance==

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.

==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 line==

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 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.

==Cheating and honor==

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.

==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 [https://docs.google.com/document/d/1_49BpcYiCXa8EO7G69lQGXeQRae7x1RrZ2R2-eJJ6io manual].

Introduction to Data Culture 2019-2020

2019-10-29T13:58:35Z

Chernik: Добавление 2 ссылок на Dropbox

==Materials==

Your grades are [https://docs.google.com/spreadsheets/d/1OtJR4Vhk8FkFHXQhJqp9VLfa9zsQ-TXGFFiF8ATmMAo/edit?usp=sharing here]
{| class="wikitable"
|-
! № !! Topic !! Slides !! Tutorial and Assignment !! Additional Materials
|-
| style="background:#eaecf0;" | '''1''' || Introduction to Data Science || https://yadi.sk/i/0f3Le1LmWT2kbw || https://yadi.sk/i/XWW37z-PH2EXug || https://bit.ly/367Ej8p
|-
| style="background:#eaecf0;" | '''2''' || || || ||
|-
| style="background:#eaecf0;" | '''3''' || || || ||
|-
| style="background:#eaecf0;" | '''4''' || || || ||
|-
| style="background:#eaecf0;" | '''5-6''' || || || ||
|-
| style="background:#eaecf0;" | '''7''' || || || ||
|}

==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.

==Communication==

All course materials, assignments, deadlines will be published on [[wiki.cs.hse.ru/Introduction_to_Data_Culture_2019-2020|[very wiki]]].

All practical announcements concerning the whole course (such as lecture cancellation) will appear on the Telegram channel https://t.me/joinchat/Du3HEUStPxVGVwnEvkzokw

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
|-
| style="background:#eaecf0;" | '''BMOL191''' || Marina Ananyeva || Egor Chernousov || Monday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL192''' || Marina Ananyeva || Valeriya Rusina || Tuesday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL193''' || Marina Ananyeva || Liana Galnutdinova || Thursday 09:00 - 10:20
|-
| style="background:#eaecf0;" | '''BMOL194''' || Marina Ananyeva || Polina Semenova || Thursday 10:30 - 11:50
|-
| style="background:#eaecf0;" | '''BMOL195''' || Ilya Abroskin || Andrey Chernikov || Monday 13:40-15:00
|-
| style="background:#eaecf0;" | '''BMOL196''' || Ilya Abroskin || Andrey Chernikov || Monday 12:10-13:30
|-
| style="background:#eaecf0;" | '''BMOL197''' || Elena Kantonistova || Mikhail Belkin || Monday 10:30-11:50
|-
| style="background:#eaecf0;" | '''BMOL198''' || Elena Kantonistova || Mikhail Belkin || Monday 09:00-10:20
|}

Links for submitting homeworks for group BMOL191:

Links for submitting homeworks for group BMOL192:

Links for submitting homeworks for group BMOL193:

[https://www.dropbox.com/request/JkVG5PXDnyJzRQ7VGp2o Practice 1]

Links for submitting homeworks for group BMOL194:

Links for submitting homeworks for group BMOL195: [https://www.dropbox.com/request/55ZgClZ7yGo2nNKIsEnS]

Links for submitting homeworks for group BMOL196: [https://www.dropbox.com/request/JQlEain1m9c9tKXCLuZy]

Links for submitting homeworks for group BMOL197:

Links for submitting homeworks for group BMOL198:

==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.

==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 and Marina Ananyeva.

==Grading==

Final Grade = 0.5*(Homework + Extra Points*) + 0.2*Control Work + 0.3*Examination Assessment

*In the beginning of each seminar students are asked to perform tests to check knowledge based on the materials of previous seminars. Each 100% correctly completed test provides the student with extra points that go towards ongoing assessment.

==Deadlines==

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

==Attendance==

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.

==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 line==

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 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.

==Cheating and honor==

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.

==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 [https://docs.google.com/document/d/1_49BpcYiCXa8EO7G69lQGXeQRae7x1RrZ2R2-eJJ6io manual].