Difference between revisions of "LU-pysem"

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Specseminārā tiks iepazīta Python programmēšanas valoda kā arī tās bibliotēkas un ietvari. Semināra mērķis ir dot ieskatu gan valodā, tās iespējās, gan plašajā pielietojumu lokā. Seminārā Python tiks lietots dažādu datu apstrādei un vizualizācijai.
Specseminārā tiks iepazīta Python programmēšanas valoda kā arī tās bibliotēkas un ietvari. Semināra mērķis ir dot ieskatu gan valodā, tās iespējās, gan plašajā pielietojumu lokā. Seminārā Python tiks lietots dažādu datu apstrādei un vizualizācijai.


 
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'''Python seminar will continue in the next (Spring 2020) semester'''
* It will take place on Fridays @ 14:30 in room 345 (LU, Raiņa bulv. 19)
* First lecture: 07-Feb-2020
* '''everyone must join Slack and fill out seminar registration form'''


''You can also join if you did not participate in the Python seminar before.'' -->
'''Project signup form''' (register by 28-Nov-2019):
* https://forms.gle/kmgjsfeiqWn2KWfv6


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* this page: http://selavo.lv/pysem
* this page: http://selavo.lv/pysem
* [https://docs.google.com/presentation/d/1yxaR_ZL3K6Z0QtOQM2dkQKXFEKGXldfy_4xsHkHWP3w/edit?usp=sharing Introduction slides (English)]
* [https://docs.google.com/presentation/d/1yxaR_ZL3K6Z0QtOQM2dkQKXFEKGXldfy_4xsHkHWP3w/edit?usp=sharing Introduction slides (English)]
* Slack channel (discussion space): https://pythonludf.slack.com
* Presentation topic signup form: https://forms.gle/eboGVK8HWVTUKgTJ9


&nbsp;
&nbsp;


'''Exams (presentation of the course project) will take place:'''
==Information and Resources==
* on 08-Jan-2021 and 22-Jan-2021 at 14:00
** location: online (Zoom)
* you can also present the course project at the last lecture (18-Dec-2020)



&nbsp;
&nbsp;


Presentation sign-up form:
'''Seminar takes place on Fridays @ 14:30'''
* https://forms.gle/joPBuJWeo4os5MXr6
* location: room 336 (LU, Raiņa bulv. 19)


&nbsp;
&nbsp;


<!-- Course registration form (Autumn 2020): https://forms.gle/FBGsJiS6CxA8eQZu5
=== Seminar materials ===


&nbsp;
''Seminar materials (slides, ...) will be placed on Github and links will be added here.''


Slack channel (discussion space): [https://join.slack.com/t/pythonludf/shared_invite/zt-h5jgmncj-HztHdIwet3Xrgxei8hgnBw link for joining Slack]
GitHub repository:
-->
* https://github.com/ValRCS/LU_PySem_2019


<!-- &nbsp;
----

* Presentation topic signup form: https://forms.gle/46Liu7bSQJKUpy31A

* Final project signup form: https://forms.gle/LrMprE4Spx3qJ6BY6
-->


&nbsp;
&nbsp;


==Course Requirements and Grading==
==Information and Resources==


&nbsp;
* '''Group Project (2-3 students preferable)'''
** 70% of course grade (mandatory)


'''Seminar takes place on Fridays @ 14:45'''
Project should be a Python program or notebook
* location: room 336 (LU, Raiņa bulv. 19)
* first seminar: 11-Sept-2020


&nbsp;
Scope: see examples shown in Sep. 20 lecture for awesome final projects


Slack channel:
* '''Presentation on a cool Python library or project (10 minutes)'''
* https://pythonludf.slack.com
** 20% of course grade (optional)


&nbsp;
Will need to sign up ahead of time


=== Seminar materials ===
* '''Participation in class'''
** 10% of course grade (optional)


Seminar materials will be published in the GitHub repository:
... or/and Python exercises solved on Project Euler, www.codewars.com, other exercise sites
* https://github.com/ValRCS/ValRCS-LU_PySem_2020_2


&nbsp;
* '''Submitted course evaluation'''

** mandatory
Last years' repositories:
* (Spring 2020) https://github.com/ValRCS/LU_PySem_2020_1
* (Autumn 2019) https://github.com/ValRCS/LU_PySem_2019


&nbsp;
&nbsp;


=== Presentations ===
==Course Project==


Presentation sign-up form:
During the course, students are required to complete a project that accomplishes a non-trivial programming / data processing task using Python tools.
* https://forms.gle/joPBuJWeo4os5MXr6
* projects can be developed in teams of 2-3 people.


&nbsp;


==Course Requirements and Grading==
Possible project topics:
* process, analyze, and/or visualize one or more datasets
* develop a simple game
* web or desktop application
* ... other ideas ...


* '''Course Project (in groups of 2-3 students or individually)''' = up to 7 points (out of 10)
Data sets can come from a variety of sources, such as kaggle.com, data.gov.lv, or faculty.
** Project should be a Python program or a Jupyter notebook
** ''Scope: project theme examples will be discussed in lectures''


&nbsp;
All processing and visualization will have to be done in the Python programming language with the appropriate Pyhon libraries.
* you can use libraries covered in the course or/and from outside the course.


* '''Presentations and participation in class''' = up to 4 points
Other topics may also be selected with prior agreement with the faculty.
** Presentation on a cool Python library or project = 1..3 points each (2 presentations possible)
*** 3 points = long and serious presentation (30 min)
*** 2 points = medium presentation (10-15 min)
*** 1 point = short presentation
*** everyone needs to present at least once
** Participation in class = 1 point
*** ... or/and Python exercises solved on Project Euler, www.codewars.com, other exercise sites


&nbsp;
Submit the project:
* https://forms.gle/kmgjsfeiqWn2KWfv6


* '''Attend at least 50% of seminars'''
=== Final project presentations ===


&nbsp;
Project presentation 08.01.2020 @ 10:00 (location to be determined)
* You can also present during the last class (22.12.2019)


* '''Submitted course evaluation in LUIS''' (mandatory)
Project presentation = 5-10 min. presentation consisting of:


&nbsp;
* Introduction (what the work is about)
* Project realization (what was programmed, what software was used)
* Demonstrations of results


''Note: sign up for presentations ahead of time''
You have to show what the project has done in practice = show code and results.


==Course Project==
Each group should send an email to uldis.bojars (at) lu.lv containing:


During the course, students are required to complete a project that accomplishes a non-trivial programming / data processing task using Python tools.
* project description (including list of group members)

* developed source code (or its URL at Github, Gitlab etc)
More information: [[LU-pysem/CourseProject|Course Project]]
* work results (e.g. Jupyter notebook)


==Why Python?==
==Why Python?==
Line 134: Line 150:


* [[User:Leo | Leo Seļāvo]] (LU DF)
* [[User:Leo | Leo Seļāvo]] (LU DF)
* Jānis Zuters (LU DF, par mašīnmācīšanos)
* Jānis Zuters (LU DF, on machine learning)
* Normunds Gruzītis (LU MII, par NLP)
* Pēteris Paikens (LU MII)
* Pēteris Paikens (LU MII)
* ...
* ...

== Grading ==

Grading will be based on your participation in the seminar (and its discussions) and your group project work.
* Participants will do a practical project using Python. Projects can be done in groups of two.

At the end of the course participants must fill out the course evaluation questionnaire in LUIS (this is a formal requirement for all courses).

Latest revision as of 15:55, 2 December 2020

Seminar: Getting things done with Python

In this seminar you will learn about the Python programming language, its libraries and frameworks.

The goal of the seminar is to give participants an insight into Python programming language and what can be done with it (including how it is used in practice). You will also learn how to use Python for data analysis and visualization. 

Specseminārā tiks iepazīta Python programmēšanas valoda kā arī tās bibliotēkas un ietvari. Semināra mērķis ir dot ieskatu gan valodā, tās iespējās, gan plašajā pielietojumu lokā. Seminārā Python tiks lietots dažādu datu apstrādei un vizualizācijai.


 

Important links:

 

Exams (presentation of the course project) will take place:

  • on 08-Jan-2021 and 22-Jan-2021 at 14:00
    • location: online (Zoom)
  • you can also present the course project at the last lecture (18-Dec-2020)


 

Presentation sign-up form:

 


 

Information and Resources

 

Seminar takes place on Fridays @ 14:45

  • location: room 336 (LU, Raiņa bulv. 19)
  • first seminar: 11-Sept-2020

 

Slack channel:

 

Seminar materials

Seminar materials will be published in the GitHub repository:

 

Last years' repositories:

 

Presentations

Presentation sign-up form:

 

Course Requirements and Grading

  • Course Project (in groups of 2-3 students or individually) = up to 7 points (out of 10)
    • Project should be a Python program or a Jupyter notebook
    • Scope: project theme examples will be discussed in lectures

 

  • Presentations and participation in class = up to 4 points
    • Presentation on a cool Python library or project = 1..3 points each (2 presentations possible)
      • 3 points = long and serious presentation (30 min)
      • 2 points = medium presentation (10-15 min)
      • 1 point = short presentation
      • everyone needs to present at least once
    • Participation in class = 1 point
      • ... or/and Python exercises solved on Project Euler, www.codewars.com, other exercise sites

 

  • Attend at least 50% of seminars

 

  • Submitted course evaluation in LUIS (mandatory)

 

Note: sign up for presentations ahead of time

Course Project

During the course, students are required to complete a project that accomplishes a non-trivial programming / data processing task using Python tools.

More information: Course Project

Why Python?

  • Python is easy to use and effective.
  • Its code is easy to read and write.
  • Python is a flexible language that can support many programming paradigms.
  • Suitable for beginners and professionals alike.
  • Popular and well-supported.
  • Used by large and small companies and organizations worldwide.
  • Used in many courses and workshops.

Contents

The seminar consists of two parts:

  • Introduction to the Python programming language (What is Python)
    • Assumption: participants know the basics of programming and, preferably, already know other programming languages
  • Practical applications of Python, with examples (Getting things done with Python)

Organizers

This seminar is lead by Uldis Bojārs and Valdis Saulespurēns.

Experts who might present guest lectures at the seminar:

  • Leo Seļāvo (LU DF)
  • Jānis Zuters (LU DF, on machine learning)
  • Pēteris Paikens (LU MII)
  • ...
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