Courses: Difference between revisions

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=== Scientific skills 1 (Veščine v znanstvenem delu 1, 2020-) ===
=== Scientific skills 1 (Veščine v znanstvenem delu 1, 2020-) ===
The course is taught to the first-year PhD students. We present basic skills and tools a research needs to have. For example, which database to use for literature research, how to define a thesis topic, how to organize a paper, how to prepare a poster, or how to present a research work.
Students need to write a short paper, give a presentation in a short limited time, and prepare a poster. All the work is related specifically to their selected topic of research.


=== Introduction to data science (Uvod v podatkovne vede, 2019-) ===
=== Introduction to data science (Uvod v podatkovne vede, 2019-) ===
This is an introductory course for the first-year data science students. Invited lecturers from industry present different aspects of work as a data scientist. During the lab sessions students are shown fundamental toolset they need as a data scientist. We cover source code management, basic infrastructure support, visualization, prototyping, reporting, databases, statistics and basics of machine learning. Students work on different projects, where the main goal is to report an added value.
We prepared a special [https://fri-datascience.github.io/course_ids online Data Science Handbook] for this course.


=== Web information extraction and retrieval (Iskanje in ekstrakcija podatkov iz spleta, 2018-) ===
=== Web information extraction and retrieval (Iskanje in ekstrakcija podatkov iz spleta, 2018-) ===

Latest revision as of 20:39, 5 August 2022

I teach courses at the University of Ljubljana, Faculty for computer and information science. Below I list current and past courses with some basic information. In case of any questions please reach out to me (see About for further information). Enrolled students can access specific information regarding current courses at http://ucilnica.fri.uni-lj.si.

Scientific skills 1 (Veščine v znanstvenem delu 1, 2020-)

The course is taught to the first-year PhD students. We present basic skills and tools a research needs to have. For example, which database to use for literature research, how to define a thesis topic, how to organize a paper, how to prepare a poster, or how to present a research work.

Students need to write a short paper, give a presentation in a short limited time, and prepare a poster. All the work is related specifically to their selected topic of research.

Introduction to data science (Uvod v podatkovne vede, 2019-)

This is an introductory course for the first-year data science students. Invited lecturers from industry present different aspects of work as a data scientist. During the lab sessions students are shown fundamental toolset they need as a data scientist. We cover source code management, basic infrastructure support, visualization, prototyping, reporting, databases, statistics and basics of machine learning. Students work on different projects, where the main goal is to report an added value.

We prepared a special online Data Science Handbook for this course.

Web information extraction and retrieval (Iskanje in ekstrakcija podatkov iz spleta, 2018-)

This course focuses on Web crawling, Web data extraction, indexing, and search. During the lab sessions students work in groups and work on three consecutive projects. First project is related to Web crawling, the second to automatic Web data extraction, and third to search and indexing.

Descriptions of the projects are available online. We also offer short tutorials on each of the projects (auditorium part only!):

2021 auditorium part of lab sessions
2021 auditorium part of lab sessions

Natural language processing (Obdelava naravnega jezika, 2016-)

Natural language processing course is project-oriented. During the lectures all the theoretical aspects along with usages are introduced. During the lab sessions we start with traditional methods in natural language processing and then continue with deep neural network models. Students work in groups on selected topics.

For the lab sessions we prepared a repository containing practical Jupyter notebooks. We also offer recordings of the first lab session in a week (auditorium part only!):

2021 auditorium lab sessions
2022 auditorium lab sessions

Fundamentals of databases (Osnove podatkovnih baz, 2014-)

This is an introductory course on databases. We introduce specifics of relational calculus and algebra, then we continue with a relational database, and finish with other database types (NoSQL) such as Neo4J, Mongo, XML databases.

Web programming (Spletno programiranje, 2017-2018)

The course was meant to dive into specifics of Web programming. We focused into backend technologies, user design, and frontend technologies.

Introduction to information systems (Osnove informacijskih sistemov, 2015-2017)

This is a first year's course where students are introduced with the MEAN stack and information systems theory.

Information systems (Informacijski sistemi, 2014-2017)

During the course we designed and implemented an information system using ASP.NET technology. We focused on different patterns of implementation of backend, database and user interface.

Introduction to programming (Uvod v programiranje, 2015-2016)

The course is meant to be an introductory course to programming in Python for the Faculy of Chemistry and Chemical Technology's students.

Data management technologies (Tehnologija upravljanja podatkov, 2014-2016)

The course was mainly focused into relational databases and data organization.

Governance in IT (Obvladovanje informatike, 2014-2016)

The course focused into IT architecture modelling. We followed COBIT, TOGAF, and used the ArchiMate tool.