Universität Wien

960021 VU Basics of IT and Data Science (2022W)

3.00 ECTS (2.00 SWS), Zertifikatskurse
Continuous assessment of course work
MIXED

Hierbei handelt es sich um ein kostenpflichtiges Angebot der Universitätslehrgänge/Zertifikatskurse des Postgraduate Center. Bitte beachten Sie, dass für die Teilnahme eine Zulassung zum Universitätslehrgang/Zertifikatskurs erforderlich ist. Weitere Informationen zu den Angeboten des Postgraduate Center finden Sie unter: https://www.postgraduatecenter.at/

Details

Language: German

Lecturers

Classes

Currently no class schedule is known.

Information

Aims, contents and method of the course

This module covers the fundamentals of IT applications and data science in terms of their potential in relation to data-driven research. After this module the students will be able to

Understand the most important concepts in Data Science, Machine Learning and Database Systems
Describe the basic concepts of programming
Know the basics of structured programming (e.g. data types, control structures, subroutines, functions …)
Describe the most important programming languages and their different aspects
Choose a suitable Integrated Development Environment (IDE) for developing own programs
Work in the Unix Shell using the most important commands for the file system and data files
Use Git/GitHub for setting up own projects, share them and find other projects
Develop small programs in Python using basic data types, control structures, functions and software libraries
Content:
Introduction to
o Data science and data-driven research
o Machine learning
o Database systems
o Programming concepts
Basics of programming:
o Unix Shell
o Git and GitHub
o Working with Python

Assessment and permitted materials

multiple-choice quiz in Moodle and practical exercises

Minimum requirements and assessment criteria

Regular attendance and an avarage grade of the test and the assignments. Grading key: 1 (excellent) to 5 (insufficient)

Examination topics

Readings and topics of the lectures

Reading list

Required Reading:
Read the following parts of the book The Fourth Paradigm: Data-Intensive Scientific Discovery , Tony Hey, Stewart Tansley, Kristin Tolle, Jim Gray, Microsoft Research, 2009, ISBN 978-0-9825442-0-4,
Available online:https://www.microsoft.com/en-us/research/publication/fourth-paradigm-data-intensive-scientific-discovery/
Introduction (Foreword, Jim Gray on eScience: A transformed scientific method)
Choose one of the essays on data science you are most interested in
Read Chapter 1 of Christopher Bishops‘ book Pattern Recognition and Machine Learning
Available online:https://www.microsoft.com/en-us/research/publication/pattern-recognition-machine-learning/
Motivation
https://towardsdatascience.com/excel-vs-sql-a-conceptual-comparison-dcfbee640c83
DB-Basics
Darwen, H. (2009). An introduction to relational database theory
Page 1-24
https://library.ku.ac.ke/wp-content/downloads/2011/08/Bookboon/IT,Programming%20and%20Web/an-introduction-to-relational-database-theory.pdf
ER-Modells
Song, I., Frohlich, K. (1995). A Practical Guide to Entity-Relationship Modeling
https://cci.drexel.edu/faculty/song/courses/info%20605/appendix/AppendixA.PDF
SQL
W3Schools (incl. try it yourself sections!)
https://www.w3schools.com/sql/sql_intro.asp
https://www.w3schools.com/sql/sql_syntax.asp
https://www.w3schools.com/sql/sql_select.asp
Lab Preparation (Important prepare this BEFORE the class starts!!)
https://docs.google.com/document/d/1mMLOWbYiAJqHtAr5L0bTFRUZJVU6guWmSnJfNlU6dzU/edit?usp=sharing
Basics in a nutshell
Busbee, K., Braunschweig, D. (2013). Programming Fundamentals - A Modular Structured Approach using C++
Page 7 (System Dev. Life Cycle) - 33
Page 37 - 41
Page 54 - 55
Page 63 - 91
https://openlibrary-repo.ecampusontario.ca/jspui/bitstream/123456789/692/3/Programming-Fundamentals-1570222270.pdf
Software Development Process
Van Castern, W. (2017). The Waterfall Model and the Agile Methodologies : A comparison by project characteristics - short
https://www.researchgate.net/publication/313768860_The_Waterfall_Model_and_the_Agile_Methodologies_A_comparison_by_project_characteristics_-_short
Rendek, L. (2020, May 28).Bash Scripting Tutorial for Beginners. Linuxconfig.Org.Retrieved August 18, 2022, fromhttps://linuxconfig.org/bash-scripting-tutorial-for-beginners(Sections Bash Shell Scripting Definition to Hello World Bash Script )
Chacon, S., & Straub, B. (2014). Pro git: Everything you need to know about Git (2nd ed.). Apress.https://git-scm.com/book/en/v2(Chapter 1)
Further Reading:

Further essays in the same book
The Fourth Paradigm 10 Years On , Tony Hey, Anne E. Trefethen, Inform. Spektrum 42(6): 441-447, 2020
Understanding Machine Learning: From Theory to Algorithms from Shai Shalev-Shwartz and Shai Ben-David; Chapters 1 & 2
Available online:https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/copy.html
F. Korth, S. Sudarshan, A. Silberschatz (2019), Database System Concepts, ISBN: 9780078022159
A. Meier, M. Kaufmann (2019), SQL & NoSQL Databases, ISBN: 9783658245498
T. Garbin (2021), Learn Coding Programming, ISBN: 9798537235354
J. Wasserberg (2020), Computer Programming for Absolute Beginners: Learn essential computer science concepts and coding techniques to kick-start your programming career , ISBN: 9781839212536
H. Bhasin (2019), Python Basics A Self-Teaching Introduction, ISBN: 978-1-683923-53-4
J. P. Mueller (2018), Beginning Programming with Python for Dummies, ISBN 978-1-119-45789-3
Newham, & Rosenblatt, B. (1998). Learning the bash Shell (2. ed., revised & updated, updated to include bash version 2.0.). O'Reilly.
Wolf, J. (2022). Shell-Programmierung. Rheinwerk Computing.https://openbook.rheinwerk-verlag.de/shell_programmierung/
Loeliger, J., &Ponuthorai, P. K., Version Control with Git. O'Reilly Media, Incorporated, 2012.
https://learngitbranching.js.org/(This is an interactive tutorial for training the branching operations in git)

Association in the course directory

Last modified: Th 08.08.2024 00:20