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.

2021W, 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, Introduction to DOPP (5.10.2021)

  2. Data wrangling on the command line, Text stream processing (12.10.2021)

  3. SciPy, NumPy, vectorisation, visualisation, benchmarking (19.10.2021)

  4. Preprocessing, Pandas (9.11.2021)

  5. Data suitability, Data biases (16.11.2021)
  6. Intro to Machine Learning (23.11.2021)

  7. Network Analysis (30.11.2021)

Exercise-related sessions

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

  • 14.12.2021, 9:00-16:00
  • 15.12.2021, 9:00-16:00

Project presentation: 25.1.2022, 9:00-18:00


 

The effort breakdown is:

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

Exercises:
    EX1 (data wrangling): 8h
    EX2 (pandas + sklearn): 12h

    EX3 (project): 37h [includes review meeting (topic + questions + work plan)]
SUM: 75h


Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue12:00 - 14:0005.10.2021 - 25.01.2022 Lectures
Tue09:00 - 13:0014.12.2021 Discussions with Groups
Wed09:00 - 11:0015.12.2021 Discussions with Groups
Wed14:00 - 16:0015.12.2021 Discussions with Groups
Data-oriented Programming Paradigms - Single appointments
DayDateTimeLocationDescription
Tue05.10.202112:00 - 14:00 Lectures
Tue12.10.202112:00 - 14:00 Lectures
Tue19.10.202112:00 - 14:00 Lectures
Tue09.11.202112:00 - 14:00 Lectures
Tue16.11.202112:00 - 14:00 Lectures
Tue23.11.202112:00 - 14:00 Lectures
Tue30.11.202112:00 - 14:00 Lectures
Tue07.12.202112:00 - 14:00 Lectures
Tue14.12.202109:00 - 13:00 Discussions with Groups
Tue14.12.202112:00 - 14:00 Lectures
Wed15.12.202109:00 - 11:00 Discussions with Groups
Wed15.12.202114:00 - 16:00 Discussions with Groups
Tue11.01.202212:00 - 14:00 Lectures
Tue18.01.202212:00 - 14:00 Lectures
Tue25.01.202212:00 - 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
21.09.2021 09:00 08.11.2021 23:00 19.11.2021 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