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


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&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)


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&nbsp;


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

Seminar materials can be found in the GitHub repository:
* https://github.com/ValRCS/LU_PySem_2019

----


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&nbsp;


Slack channel (discussion space): [https://join.slack.com/t/pythonludf/shared_invite/zt-h5jgmncj-HztHdIwet3Xrgxei8hgnBw link for joining Slack]
==Course Requirements and Grading==
-->


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


* Presentation topic signup form: https://forms.gle/46Liu7bSQJKUpy31A
Project should be a Python program or notebook


* Final project signup form: https://forms.gle/LrMprE4Spx3qJ6BY6
Scope: see examples shown in Sep. 20 lecture for awesome final projects
-->


&nbsp;
* '''Presentation on a cool Python library or project (10 minutes)'''
** 20% of course grade (optional)


==Information and Resources==
Will need to sign up ahead of time


&nbsp;
* '''Participation in class'''
** 10% of course grade (optional)


'''Seminar takes place on Fridays @ 14:45'''
... or/and Python exercises solved on Project Euler, www.codewars.com, other exercise sites
* location: room 336 (LU, Raiņa bulv. 19)
* first seminar: 11-Sept-2020


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

** mandatory
Slack channel:
* https://pythonludf.slack.com


&nbsp;
&nbsp;


=== Seminar materials ===
==Course Project==


Seminar materials will be published in the GitHub repository:
During the course, students are required to complete a project that accomplishes a non-trivial programming / data processing task using Python tools.
* https://github.com/ValRCS/ValRCS-LU_PySem_2020_2
* projects can be developed in teams of 2-3 people.


&nbsp;


Last years' repositories:
Possible project topics:
* (Spring 2020) https://github.com/ValRCS/LU_PySem_2020_1
* process, analyze, and/or visualize one or more datasets
* (Autumn 2019) https://github.com/ValRCS/LU_PySem_2019
* develop a simple game
* web or desktop application
* ... other ideas ...


&nbsp;
Data sets can come from a variety of sources, such as kaggle.com, data.gov.lv, or faculty.


=== Presentations ===
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.


Presentation sign-up form:
Other topics may also be selected with prior agreement with the faculty.
* https://forms.gle/joPBuJWeo4os5MXr6


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


==Course Requirements and Grading==
=== Final project presentations ===


* '''Course Project (in groups of 2-3 students or individually)''' = up to 7 points (out of 10)
Project presentation 08.01.2020 (time and location to be determined)
** Project should be a Python program or a Jupyter notebook
* You can also present during the last class (22.12.2019)
** ''Scope: project theme examples will be discussed in lectures''


&nbsp;
&nbsp;


* '''Presentations and participation in class''' = up to 4 points
'''Project presentation = 5-10 min. presentation consisting of:'''
** 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;
* Introduction (what the work is about)
* Project realization (what was programmed, what software was used)
* Demonstrations of results


* '''Attend at least 50% of seminars'''
You have to show what the project has done in practice = show code and results.


&nbsp;
&nbsp;


* '''Submitted course evaluation in LUIS''' (mandatory)
'''Each group should send an email to uldis.bojars (at) lu.lv containing:'''


&nbsp;
* project description (including list of group members)

* developed source code (or its URL at Github, Gitlab etc)
''Note: sign up for presentations ahead of time''
* work results (e.g. Jupyter notebook)

==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: [[LU-pysem/CourseProject|Course Project]]


==Why Python?==
==Why Python?==
Line 136: 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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