188.995 Data-oriented Programming Paradigms
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020W, VU, 2.0h, 3.0EC
TUWEL

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise
  • Format: Distance Learning

Learning outcomes

After successful completion of the course, students are able to program in Python in a data-oriented way, using SciPy, NumPy and Pandas; explain the fundamentals of machine learning and network analysis, and implement a Data Science project.

Subject of course

The following topics are covered in the lectures:

  • Introduction to Data-Oriented Programming Paradigms
  • Python
  • SciPy, NumPy, vectorisation, execution performance measurement
  • Data preparation, structuring, fusion with Pandas
  • Data Science solution approaches and case studies
  • Introduction to machine learning
  • Introduction to network analysis

Teaching methods

lectures about the fundamentals

3 practical exercises (Exercises 1 and 2 are done individually, Exercise 3 is done in a group)

Mode of examination

Immanent

Additional information

The link to the online lectures is on TUWEL.

 

Syllabus

All Lectures on Tuesday 12:00 c.t.-13:45.

  1. Kickoff-Session, data science process, community, solution examples, Python introduction [Hanbury] (6.10.2020)

  2. Introduction to DOPP [Hanbury] (13.10.2020)

  3. SciPy, NumPy, vectorisation, visualisation, benchmarking [Piroi] (27.10.2020)

  4. Preprocessing, Pandas [Piroi] (3.11.2020)

  5. Intro to Machine Learning [Hanbury] (17.11.2020)

  6. Network Analysis [Hanbury] (1.12.2020)

Exercise-related sessions

Review meetings for exercise 3 (15 minutes for each group):

  • 15.12.2020, 9:00-13:00
  • 16.12.2020, 9:00-11:00 and 13:00-15:00

Project presentation: 27.1.2020, 9:00-16:00

 

The effort breakdown is:

Python tutorial: 4h
Lectures: 7 sessions @ 2h: 14h

Exercises:
    EX1 (data wrangling): 5h
    EX2 (pandas + sklearn): 10h

    EX3 (project): 42h [includes review meeting (topic + questions + work plan)]
SUM: 75h


Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue12:00 - 14:0006.10.2020 - 26.01.2021 Lectures
Tue09:00 - 13:0015.12.2020 (LIVE)Discussions with Groups
Wed09:00 - 11:0016.12.2020 (LIVE)Discussions with Groups
Wed14:00 - 16:0016.12.2020 (LIVE)Discussions with Groups
Wed09:00 - 18:0027.01.2021FAV Hörsaal 1 - INF Presentations
Data-oriented Programming Paradigms - Single appointments
DayDateTimeLocationDescription
Tue06.10.202012:00 - 14:00 Lectures
Tue13.10.202012:00 - 14:00 Lectures
Tue20.10.202012:00 - 14:00 Lectures
Tue27.10.202012:00 - 14:00 Lectures
Tue03.11.202012:00 - 14:00 Lectures
Tue10.11.202012:00 - 14:00 Lectures
Tue17.11.202012:00 - 14:00 Lectures
Tue24.11.202012:00 - 14:00 Lectures
Tue01.12.202012:00 - 14:00 Lectures
Tue15.12.202009:00 - 13:00 Discussions with Groups
Tue15.12.202012:00 - 14:00 Lectures
Wed16.12.202009:00 - 11:00 Discussions with Groups
Wed16.12.202014:00 - 16:00 Discussions with Groups
Tue12.01.202112:00 - 14:00 Lectures
Tue19.01.202112:00 - 14:00 Lectures
Tue26.01.202112:00 - 14:00 Lectures

Examination modalities

Three practical exercises. The third exercise requires a report, Jupyter Notebook, and presentation of the results.

Course registration

Begin End Deregistration end
22.09.2020 09:00 09.11.2020 23:00 20.11.2020 23:55

Curricula

Study CodeSemesterPrecon.Info
045 006 Digital Skills STEOP
Course requires the completion of the introductory and orientation phase
066 645 Data Science
066 645 Data Science
066 646 Computational Science and Engineering
066 926 Business Informatics
175 FW Elective Courses - Economics and Computer Science
880 FW Elective Courses - Computer Science

Literature

No lecture notes are available.

Language

English