Difference between revisions of "LU-pysem"

From DiLab
Jump to: navigation, search
(Description for Python seminar 2019)
(Final project presentations)
(17 intermediate revisions by 2 users not shown)
Line 10: Line 10:
 
 


'''Presentation topic''' signup form (fill it out by 28-Oct-2019):
==Information and Resources==
* https://forms.gle/eboGVK8HWVTUKgTJ9


 
 


'''Important links:'''
'''Seminar takes place on Fridays @ 14:30'''
* this page: http://selavo.lv/pysem
* location: room 336 (LU, Raiņa bulv. 19)
* [https://docs.google.com/presentation/d/1yxaR_ZL3K6Z0QtOQM2dkQKXFEKGXldfy_4xsHkHWP3w/edit?usp=sharing Introduction slides (English)]
* Slack channel (discussion space): https://pythonludf.slack.com


 
 


==Information and Resources==
----


 
This page: http://selavo.lv/pysem


'''Seminar takes place on Fridays @ 14:30'''
Discussion space:
* location: room 336 (LU, Raiņa bulv. 19)
* '''join our Slack channel: http://bit.ly/py-df-2019 '''
** all participants should join seminar's Slack channel
** the link (for joining) is valid until 04-Oct-2019. if it does not work, please ask the organizers.
* https://pythonludf.slack.com


 
 
Line 34: Line 34:


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

GitHub repository:
* https://github.com/ValRCS/LU_PySem_2019


----
----
Line 39: Line 42:
 
 


==Course Requirements and Grading==
===Why Python?===

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

Project should be a Python program or notebook

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

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

Will need to sign up ahead of time

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

... or/and Python exercises solved on Project Euler, www.codewars.com, other exercise sites

* '''Submitted course evaluation'''
** mandatory

 

==Course Project==

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


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

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

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.

Other topics may also be selected with prior agreement with the faculty.

Submit the project:
* ''... submission link will be added here ...''

=== Final project presentations ===

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

Project presentation = 5-10 min. presentation consisting of:

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

You have to show what the project has done in practice = show code and results.

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

* project description (including list of group members)
* developed source code (or its URL at Github, Gitlab etc)
* work results (e.g. Jupyter notebook)

==Why Python?==
* Python is easy to use and effective.
* Python is easy to use and effective.
* Its code is easy to read and write.
* Its code is easy to read and write.
Line 48: Line 116:
* Used in many courses and workshops.
* Used in many courses and workshops.


=== Contents ===
== Contents ==
The seminar consists of two parts:
The seminar consists of two parts:
* Introduction to the Python programming language (What is Python)
* Introduction to the Python programming language (What is Python)
Line 58: Line 126:
*** Libraries: NumPy, SciPy, Pandas, Matplotlib, Flask, ...
*** Libraries: NumPy, SciPy, Pandas, Matplotlib, Flask, ...


=== Organizers ===
== Organizers ==


This seminar is lead by Uldis Bojārs and Valdis Saulespurēns.
This seminar is lead by Uldis Bojārs and Valdis Saulespurēns.
Line 64: Line 132:
Experts who might present guest lectures at the seminar:
Experts who might present guest lectures at the seminar:


* Leo Seļāvo (LU DF)
* [[User:Leo | Leo Seļāvo]] (LU DF)
* Jānis Zuters (LU DF, par mašīnmācīšanos)
* Jānis Zuters (LU DF, par mašīnmācīšanos)
* Normunds Gruzītis (LU MII, par NLP)
* Normunds Gruzītis (LU MII, par NLP)
Line 70: Line 138:
* ...
* ...


=== Grading ===
== Grading ==


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


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

Revision as of 23:28, 8 November 2019

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.

 

Presentation topic signup form (fill it out by 28-Oct-2019):

 

Important links:

 

Information and Resources

 

Seminar takes place on Fridays @ 14:30

  • location: room 336 (LU, Raiņa bulv. 19)

 

Seminar materials

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

GitHub repository:


 

Course Requirements and Grading

  • Group Project (2-3 students preferable)
    • 70% of course grade (mandatory)

Project should be a Python program or notebook

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

  • Presentation on a cool Python library or project (10 minutes)
    • 20% of course grade (optional)

Will need to sign up ahead of time

  • Participation in class
    • 10% of course grade (optional)

... or/and Python exercises solved on Project Euler, www.codewars.com, other exercise sites

  • Submitted course evaluation
    • mandatory

 

Course Project

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

  • projects can be developed in teams of 2-3 people.


Possible project topics:

  • process, analyze, and/or visualize one or more datasets
  • develop a simple game
  • web or desktop application
  • ... other ideas ...

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

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.

Other topics may also be selected with prior agreement with the faculty.

Submit the project:

  • ... submission link will be added here ...

Final project presentations

Project presentation 08.01.2020 @ 10:00 (location to be determined)

  • You can also present during the last class (22.12.2019)

Project presentation = 5-10 min. presentation consisting of:

  • Introduction (what the work is about)
  • Project realization (what was programmed, what software was used)
  • Demonstrations of results

You have to show what the project has done in practice = show code and results.

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

  • project description (including list of group members)
  • developed source code (or its URL at Github, Gitlab etc)
  • work results (e.g. Jupyter notebook)

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, par mašīnmācīšanos)
  • Normunds Gruzītis (LU MII, par NLP)
  • 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).