pub:teaching:start
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- | ====== Teaching ====== | + | ~~NOTOC~~ |
- | ===== Labs and equipment ===== | + | {{page> pub: |
- | At the team disposal are two modern computer labs. In the labs a heterogeneous networking environment is provided with both GNU/Linux as well as other environments. | + | ====== GEIST Teaching ====== |
- | In 2008 a new robotics lab ([[http:// | + | ===== GRIS ===== |
+ | | ||
- | {{gallery> | + | ===== Courses |
- | + | ||
- | ===== Teaching materials | + | |
- | ==== GRIS ==== | + | |
- | - a.k.a. GEISTa Reguły Interakcji ze Studentami: [[: | + | |
- | ==== AI wiki ==== | + | Current lists of courses taught can be found in the JU USOSweb system: |
- | [[http://ai.ia.agh.edu.pl/wiki/|{{ :pub:teaching:aiwiki2.png|AIwiki logo}}]] | + | * [[pub: |
- | [[http://ai.ia.agh.edu.pl/wiki/|AI wiki]] is a system used for coordinating the didactic activities. | + | * [[pub: |
- | These include the teaching instructions, | + | * [[pub:about_us:kkt|dr inż. Krzysztof Kutt]]: [[https://www.usosweb.uj.edu.pl/kontroler.php? |
- | GEIST members have developed some [[http:// | + | Details of the content and credit rules for each course can be found in the [[https://sylabus.uj.edu.pl/en/|JU Sylabus]]. |
- | They mainly deal with [[http:// | + | |
- | Other subjects taught by GEIST include: [[http:// | ||
- | The courses are taught in Polish, so most of the instructions are in Polish only. However, some course materials are bilingual and other have only an English version. | + | ===== Human-AI Laboratory (HAL) ===== |
- | ==== Personal wikis ==== | + | |
- | One can find other teaching materials on the GEIST members' | + | |
- | * [[http:// | + | |
- | * [[http:// | + | |
- | * [[http:// | + | |
- | * [[http:// | + | |
+ | A didactic laboratory established in 2021 at the Jagiellonian University under the project **HAL2021: Human-AI Laboratory** ([[https:// | ||
+ | The laboratory includes the equipment needed to conduct practical laboratory classes focusing on **modern methods of human-machine interaction based on artificial intelligence methods**. In particular, the laboratory is equipped with: | ||
+ | * 3x biosignalsplux Explorer **physiological signal measurement kits** | ||
+ | * **Hardware acceleration modules for AI**: 2x Groove AI Hat (for Raspberry Pi), 2x Intel Neural Compute Stick 2 (with USB interface), 4x Google Coral Dev Board (standalone boards) | ||
+ | * 4x **Raspberry Pi** 4B minicomputers | ||
+ | * 5x **Android phones** with NPU module dedicated to machine learning and with ARcore SDK support for augmented reality solutions (XIAOMI Mi 10 Lite 5G 6/128 GB) | ||
+ | * 2x 1TB **external drives** for data collected in experiments | ||
+ | |||
+ | {{gallery> | ||
+ | |||
+ | Equipment from the lab is used in the following courses, among others: | ||
+ | * //AI workshop I & II// (WFAIS.IF-XG322.0, | ||
+ | * // | ||
+ | * //Ambient Intelligence Systems// (WFAIS.IF-XG323.0) | ||
+ | * //Data Mining workshop// (WFAIS.IF-X217.0) |
pub/teaching/start.1349098703.txt.gz · Last modified: 2012/10/01 13:38 by wta