retrieve:
Return the details about the given Event id.

list:
List all Event objects.

GET /api/v1/events/?format=api&offset=50&ordering=event__end_date
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

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            "title": "Topological Data Analysis for Gait Pattern Classification",
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            "description": "<p>The classification of gait patterns is an important challenge in movement analysis, as it supports clinical assessment and decision-making by enabling diagnosis and severity stratification. In this talk, I will discuss the potential of Topological Data Analysis (TDA) for gait pattern classification. Unlike conventional approaches that rely on explicit detection of Gait Events (GEs) to compute Spatiotemporal Gait Parameters (SGPs), TDA characterises the global structure of gait signals directly, capturing relationships and patterns in the data without requiring GEs. This is particularly relevant in real-world settings, where GE detection can be diQicult due to heterogeneity in walking conditions and gait patterns, potentially biasing clinically relevant metrics and, consequently, decision-making.<br>\r\nWithin our department, preliminary results have shown that TDA-based features can achieve classification performance comparable to that of SGPs in fall-risk assessment. These findings suggest that topology oQers a competitive alternative for representing gait data, with the potential to better handle variability across subjects and pathological<br>\r\nconditions.<br>\r\nBuilding on these results, we plan to further extend the TDA framework in two directions. First, we aim to investigate time-aware topological methods to better capture the<br>\r\ntemporal structure of gait signals. Second, we will explore Topological Deep Learning (TDL) approaches to reduce reliance on handcrafted design choices and potentially<br>\r\nimprove classification performance. By combining the robustness of topology with datadriven representation learning, this work seeks to provide robust tools for the classification of typical and pathological gait patterns.<br>\r\n </p>",
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            "speaker": "Elena Botti, Vrije Universiteit Brussel (VUB)",
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            "contact": "Maroussia Schaffner",
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            "id": 70900,
            "title": "FAIR Data Management of Theoretical Spectroscopy and Green’s Function Methods",
            "slug": "fair-data-management-of-theoretical-spectroscopy-a",
            "event_url": "https://memento.epfl.ch/event/fair-data-management-of-theoretical-spectroscopy-a",
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            "start_date": "2026-04-20",
            "end_date": "2026-04-24",
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            "description": "<p>You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: <a href=\"https://www.cecam.org/workshop-details/fair-data-management-of-theoretical-spectroscopy-and-greens-function-methods-1377\">https://www.cecam.org/workshop-details/fair-data-management-of-theoretical-spectroscopy-and-greens-function-methods-1377</a>.<br>\r\n<br>\r\nRegistration is required to attend the full event, take part in the social activities and present a poster at the poster session (if any).  However, the EPFL community is welcome to attend specific lectures without registration if the topic is of interest to their research. Do not hesitate to contact the <a href=\"mailto:[email protected]\">CECAM Event Manager</a> if you have any question.<br>\r\n<br>\r\n<strong>Description</strong><br>\r\n<br>\r\nBig-data-driven methodologies have emerged as a fundamental paradigm of science, but require an enormous amount of resources to achieve their promised impact. The FAIR (Findable, Accessible, Interoperable, and Reusable) data principles [1] ensure that scientific data can be shared and reutilized, providing an efficient route for accumulating data and taking advantage of these powerful techniques. FAIR data management allows essential knowledge to be systematically extracted from data, accelerating discoveries and innovations across various domains [2]. Furthermore, open science is essential for the verifiability and reproducibility of results and has been a topic of major discussion over the last decade. In materials science, data-driven methodologies, coupled with the appropriate FAIR data management practices, are invaluable for the discovery of new materials due to the vast combinatorial space of chemical systems that emerge from the periodic table [3, 4]. Such methodologies have been successfully applied, e.g., to design and predict new materials with desired properties using ab-initio ground state simulations, i.e., data generated from Density Functional Theory (DFT) calculations [5]. However, there remains a critical gap in replicating this success in the context of other simulation frameworks. <br>\r\nTheoretical spectroscopy and Green's function method simulations [6, 7], including data simulated using the GW approximation, Time-Dependent Density Functional Theory (TDDFT), the Bethe-Salpeter equation (BSE), Dynamical Mean-Field Theory (DMFT), and Korringa-Kohn-Rostoker (KKR), pose especially difficult challenges in the context of FAIR data management. These simulations not only involve extensive computational resources and produce large datasets with associated complex workflows but are also executed using a large variety of public and in-house simulation software. At the same time, these methodologies are essential for understanding excited state properties of complex materials; they are more accurate than DFT calculations and provide better comparisons with experimental results since they incorporate excited states and electronic correlation effects in a more consistent manner [8]. <br>\r\nThere has recently been a number of individual efforts to improve the accessibility of  data produced by theoretical spectroscopy and Green’s function methods through the usage of publicly accessible databases. For example, the Computational Materials Repository (CMR) [9] contains several individual databases, amongst which the Computational 2D Materials Database (C2DB) [10] contains GW and BSE data for a specific set of parameters and properties. The MaterialsCloud [11] database has some individual datasets published for these methodologies, however there is not a clear data structure for them. The NIST-JARVIS [12] database has a specific app for BeyondDFT simulations with DMFT data, but only for a specific simulation code. By making datasets findable, these efforts aim to avoid redundant computations and thus build upon existing work more efficiently. While these efforts represent an important step in the right direction, they fall short of fully achieving their goal due to a continued lack of consistency (i.e., <em>interoperability</em>) between individual databases. Moreover, these self-managed databases typically lack the ability to store the complete provenance of the simulated workflow, which is essential to ensure reproducibility. <br>\r\nRecently, FAIRmat [13], a consortium of the German research data infrastructure (NFDI) association, was formed to construct a scalable data infrastructure for Materials Science that can be easily customized for individual communities. This infrastructure consists of a primary software and repository called NOMAD [14]—a free web-service that enables the organization, analysis, sharing, and publishing of materials science data. One of the tasks within FAIRmat’s scope is to build support for theoretical spectroscopy and Green’s function simulations within NOMAD. Support for several of these methodologies have now been successfully built, and there already exists over 10 000 entries in the NOMAD repository containing GW [15], BSE [16], and DMFT [17] data, along with the full provenance of the corresponding complex workflows. The next step to developing a FAIR data infrastructure for these methods is to tackle the interoperability problem.<br>\r\nInteroperability within this domain is extremely challenging due to the heterogeneous character of theoretical spectroscopy and Green’s function simulations. Consequently, the adoption of common structures (e.g., describing the Green’s function, the self-energy, or the dielectric function) is the key for improving interoperability. Thus, various members of the community, including method developers, materials and data scientists, and data management experts, must come together to reach a consensus on specific common data structures.<br>\r\n<br>\r\n<strong>References</strong><br>\r\n<br>\r\n<a href=\"https://cmr.fysik.dtu.dk/\" target=\"_blank\">[1] Computational Materials Repository (CMR) website</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41467-024-48169-5\" target=\"_blank\">[2] S. Di Cataldo, P. Worm, J. Tomczak, L. Si, K. Held, Nat. Commun., <strong>15</strong>, 3952 (2024)</a><br>\r\n<a href=\"http://dx.doi.org/10.1103/physrevmaterials.8.013801\" target=\"_blank\">[3] F. Meng, B. Maurer, F. Peschel, S. Selcuk, M. Hybertsen, X. Qu, C. Vorwerk, C. Draxl, J. Vinson, D. Lu, Phys. Rev. Materials, <strong>8</strong>, 013801 (2024)</a><br>\r\n<a href=\"http://dx.doi.org/10.1021/acs.jctc.5b00453\" target=\"_blank\">[4] M. van Setten, F. Caruso, S. Sharifzadeh, X. Ren, M. Scheffler, F. Liu, J. Lischner, L. Lin, J. Deslippe, S. Louie, C. Yang, F. Weigend, J. Neaton, F. Evers, P. Rinke, J. Chem. Theory Comput., <strong>11</strong>, 5665-5687 (2015)</a><br>\r\n<a href=\"http://dx.doi.org/10.21105/joss.05388\" target=\"_blank\">[5] M. Scheidgen, L. Himanen, A. Ladines, D. Sikter, M. Nakhaee, Á. Fekete, T. Chang, A. Golparvar, J. Márquez, S. Brockhauser, S. Brückner, L. Ghiringhelli, F. Dietrich, D. Lehmberg, T. Denell, A. Albino, H. Näsström, S. Shabih, F. Dobener, M. Kühbach, R. Mozumder, J. Rudzinski, N. Daelman, J. Pizarro, M. Kuban, C. Salazar, P. Ondračka, H. Bungartz, C. Draxl, JOSS., <strong>8</strong>, 5388 (2023)</a><br>\r\n<a href=\"https://www.fairmat-nfdi.eu/fairmat/\" target=\"_blank\">[6] FAIRmat website</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41524-020-00440-1\" target=\"_blank\">[7] K. Choudhary, K. Garrity, A. Reid, B. DeCost, A. Biacchi, A. Hight Walker, Z. Trautt, J. Hattrick-Simpers, A. Kusne, A. Centrone, A. Davydov, J. Jiang, R. Pachter, G. Cheon, E. Reed, A. Agrawal, X. Qian, V. Sharma, H. Zhuang, S. Kalinin, B. Sumpter, G. Pilania, P. Acar, S. Mandal, K. Haule, D. Vanderbilt, K. Rabe, F. Tavazza, npj. Comput. Mater., <strong>6</strong>, 173 (2020)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41597-020-00637-5\" target=\"_blank\">[8] L. Talirz, S. Kumbhar, E. Passaro, A. Yakutovich, V. Granata, F. Gargiulo, M. Borelli, M. Uhrin, S. Huber, S. Zoupanos, C. Adorf, C. Andersen, O. Schütt, C. Pignedoli, D. Passerone, J. VandeVondele, T. Schulthess, B. Smit, G. Pizzi, N. Marzari, Sci. Data., <strong>7</strong>, 299 (2020)</a><br>\r\n<a href=\"http://dx.doi.org/10.1088/2053-1583/aacfc1\" target=\"_blank\">[9] S. Haastrup, M. Strange, M. Pandey, T. Deilmann, P. Schmidt, N. Hinsche, M. Gjerding, D. Torelli, P. Larsen, A. Riis-Jensen, J. Gath, K. Jacobsen, J. Jørgen Mortensen, T. Olsen, K. Thygesen, 2D Mater., <strong>5</strong>, 042002 (2018)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/sdata.2016.18\" target=\"_blank\">[10] M. Wilkinson, M. Dumontier, I. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, J. Boiten, L. da Silva Santos, P. Bourne, J. Bouwman, A. Brookes, T. Clark, M. Crosas, I. Dillo, O. Dumon, S. Edmunds, C. Evelo, R. Finkers, A. Gonzalez-Beltran, A. Gray, P. Groth, C. Goble, J. Grethe, J. Heringa, P. ’t Hoen, R. Hooft, T. Kuhn, R. Kok, J. Kok, S. Lusher, M. Martone, A. Mons, A. Packer, B. Persson, P. Rocca-Serra, M. Roos, R. van Schaik, S. Sansone, E. Schultes, T. Sengstag, T. Slater, G. Strawn, M. Swertz, M. Thompson, J. van der Lei, E. van Mulligen, J. Velterop, A. Waagmeester, P. Wittenburg, K. Wolstencroft, J. Zhao, B. Mons, Sci. Data., <strong>3</strong>, 160018 (2016)</a><br>\r\n<a href=\"https://www.sciencedirect.com/journal/comptes-rendus-physique/vol/10/issue/6\" target=\"_blank\">[11] L. Reining et al., Comptes Rendus Physique 10, 6 (2009)</a><br>\r\n<a href=\"http://dx.doi.org/10.1088/2516-1075/ad48ec\" target=\"_blank\">[12] V. Blum, R. Asahi, J. Autschbach, C. Bannwarth, G. Bihlmayer, S. Blügel, L. Burns, T. Crawford, W. Dawson, W. de Jong, C. Draxl, C. Filippi, L. Genovese, P. Giannozzi, N. Govind, S. Hammes-Schiffer, J. Hammond, B. Hourahine, A. Jain, Y. Kanai, P. Kent, A. Larsen, S. Lehtola, X. Li, R. Lindh, S. Maeda, N. Makri, J. Moussa, T. Nakajima, J. Nash, M. Oliveira, P. Patel, G. Pizzi, G. Pourtois, B. Pritchard, E. Rabani, M. Reiher, L. Reining, X. Ren, M. Rossi, H. Schlegel, N. Seriani, L. Slipchenko, A. Thom, E. Valeev, B. Van Troeye, L. Visscher, V. Vlcek, H. Werner, D. Williams-Young, T. Windus, Electron. Struct., (2024)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41597-023-02501-8\" target=\"_blank\">[13] L. Ghiringhelli, C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C. Koch, M. Kühbach, A. Ladines, P. Lambrix, M. Himmer, S. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll, M. Scheffler, Sci. Data., <strong>10</strong>, 626 (2023)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41524-019-0221-0\" target=\"_blank\">[14] J. Schmidt, M. Marques, S. Botti, M. Marques, npj. Comput. Mater., <strong>5</strong>, 83 (2019)</a><br>\r\n<a href=\"http://dx.doi.org/10.1002/advs.201900808\" target=\"_blank\">[15] L. Himanen, A. Geurts, A. Foster, P. Rinke, Advanced Science, <strong>6</strong>, (2019)</a><br>\r\n<a href=\"http://dx.doi.org/10.1038/s41586-022-04501-x\" target=\"_blank\">[16] M. Scheffler, M. Aeschlimann, M. Albrecht, T. Bereau, H. Bungartz, C. Felser, M. Greiner, A. Groß, C. Koch, K. Kremer, W. Nagel, M. Scheidgen, C. Wöll, C. Draxl, Nature, <strong>604</strong>, 635-642 (2022)</a><br>\r\n<a href=\"http://dx.doi.org/10.1557/mrs.2018.208\" target=\"_blank\">[17] C. Draxl, M. Scheffler, MRS Bull., <strong>43</strong>, 676-682 (2018)</a></p>",
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            "description": "<p>Thesis Director: Prof. A. L. A. Persat,<br>\r\nBiotechnology and Bioengineering doctoral program<br>\r\nThesis Nr. 11340<br>\r\n<br>\r\nTo take part in the public defense, please contact directly the speaker</p>",
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        {
            "id": 71223,
            "title": "How to Prepare Successful Grant Proposals: a course for Postdocs",
            "slug": "how-to-prepare-successful-grant-proposals-a-cou-12",
            "event_url": "https://memento.epfl.ch/event/how-to-prepare-successful-grant-proposals-a-cou-12",
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            "start_date": "2026-04-24",
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            "start_time": null,
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            "description": "<strong>The Research Office is offering a course for EPFL postdoctoral researchers and senior PhD students entitled “How to prepare successful grant proposals”.</strong><br>\r\n<br>\r\nThis course will teach participants where to look for appropriate fellowship and research funding opportunities, the ins and outs of the application process itself, and how to prepare a written proposal. It is primarily intended for EPFL postdocs and senior PhD students who want to start preparing their postdoctoral fellowship applications.<br>\r\n<br>\r\n<strong>When: Friday 24<sup>th</sup> April 2026, 11:30-3 pm, in person, </strong><a href=\"https://plan.epfl.ch/?dim_floor=4&amp;lang=en&amp;dim_lang=en&amp;tree_groups=centres_nevralgiques_grp%2Cmobilite_acces_grp%2Crestauration_et_commerces_grp%2Censeignement%2Cservices_campus_grp%2Cequipements_grp&amp;tree_group_layers_centres_nevralgiques_grp=&amp;tree_group_layers_mobilite_acces_grp=metro&amp;tree_group_layers_restauration_et_commerces_grp=&amp;tree_group_layers_enseignement=guichet_etudiants&amp;tree_group_layers_services_campus_grp=information_epfl&amp;tree_group_layers_equipements_grp=&amp;baselayer_ref=grp_backgrounds&amp;map_x=2532712&amp;map_y=1152288&amp;map_zoom=14\"><strong>BC 420</strong></a><strong> (Lausanne Campus). Lunch will be provided.</strong><br>\r\n<br>\r\nParticipants can apply to a follow-up “Writing Clinic” during which they will develop their own research proposal with live feedback from their peers. Dates: 25<sup>th </sup>May, 9<sup>th</sup> and 23<sup>rd</sup> June 2026.<br>\r\n<br>\r\nRegistration is now open and interested postdocs and senior PhD students should <a href=\"https://forms.office.com/e/0HxeCin2xA\">register for the course</a> by Monday 20<sup>th</sup> April 2026 midday. Further details on the course can be found <a href=\"https://www.epfl.ch/research/management-support/grant-writing/trainings/postdoc/\">here</a>.<br>\r\n<br>\r\nAny questions can be directed to the <a href=\"mailto:[email protected]\">EPFL Research Office</a>",
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        {
            "id": 71272,
            "title": "An Artificial Sphincter based on Dielectric Elastomer Actuators in the context of Urinary Incontinence",
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            "description": "<p>Thesis Directors: Prof. Y. Perriard, Dr Y. R. C. Civet<br>\r\nAdvanced Manufacturing doctoral program<br>\r\nThesis Nr. 11322<br>\r\n<br>\r\nTo take part in the public defense, please contact directly the speaker</p>",
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            "creation_date": "2026-03-02T10:55:01",
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            "id": 71448,
            "title": "Topological properties of rough fluids and plasmas",
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            "start_date": "2026-04-24",
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            "description": "<p>Abstract:<br>\r\nAs anticipated by Onsager's conjecture, low-regularity solutions of the Euler equations exhibit greater flexibility than classical solutions. In the first part of this talk we focus on steady solutions, showing that in the low-regularity regime their streamlines can realize any prescribed topology, a phenomenon that cannot occur for classical solutions. The key tool is a novel implementation of convex integration that preserves the topology of the streamlines throughout the iteration. In the second part we extend these ideas to the MHD equations, constructing continuous weak solutions with constant nonzero helicity that nevertheless fail to conserve energy and cross helicity.</p>",
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        {
            "id": 71450,
            "title": "Visitors Talk: Mary Helen Immordino-Yang, University of Southern California",
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            "lang": "en",
            "start_date": "2026-04-24",
            "end_date": "2026-04-24",
            "start_time": "13:00:00",
            "end_time": "14:00:00",
            "description": "<p>Hosted by Solange Denervaud, CIBM Flagship Project Officer, we are pleased  to invite you to attend the CIBM Visitors Talk on April 24th at 13:00 CEST by Mary Helen Immordino-Yang from the University of Southern California who will be sharing on “Longitudinal neurodevelopmental correlates of mid-adolescents’ psychosocial processing: A path to young adult wellbeing?”.<br>\r\n<br>\r\n<strong>Abstract</strong><br>\r\nCombining open-ended interviews (outside the scanner) with structural, trial-by-trial, and resting-state functional MRI neuroimaging, we examined real-time functional neural dynamics underlying diverse urban mid-adolescents’ cognitive and emotional engagement with compelling social stories at two time-points, two years apart. We found that the patterns of longitudinal change in neural network dynamics predicted psychosocial outcomes five years later in young adulthood.<br>\r\nWe found that “transcendent thinking” – seeing situations not just in terms of X happened to person A, which makes me feel thusly, but in terms of the larger societal and contextual forces that shaped how Person A was treated and how Person A reacted, the broader implications and lessons one can draw from that situation, and the larger issues it exemplifies or reveals—correlated with a particular set of neural activity dynamics and predicted future structural and functional neural development across the subsequent two years, controlling for the starting state of neural development, and independent of IQ and SES. Transcendent thinking also countered negative effects of exposure to community violence on structural brain development.<br>\r\nThe neural development predicted by transcendent thinking (the changes in the brain across the 2-year period) in turn predicted young adult identity strength, self-liking, relationship satisfaction, and achievement 5 years later.<br>\r\nThese findings reveal a novel predictor of neural development across mid-adolescence, and underscore the active role adolescents play in their own brain development through the meaning they make of the social world. Implications for secondary education and pedagogy will be discussed.<br>\r\n<br>\r\n </p>",
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            "cancel_reason": "",
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            "organizer": "<a href=\"https://cibm.ch\">CIBM Center for Biomedical Imaging</a>",
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            "keywords": "neuroscience, psycology, education",
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        {
            "id": 71516,
            "title": "Xenon Dynamic Nuclear Polarization: from Spin Dynamics to In-Vivo Applications",
            "slug": "xenon-dynamic-nuclear-polarization-from-spin-dyn-2",
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            "description": "<p>Thesis Directors: Prof. R. Gruetter, Dr A. Capozzi<br>\r\nPhysics doctoral program<br>\r\nThesis Nr. 11427<br>\r\n<br>\r\nTo take part in the public defense, please contact directly the speaker</p>",
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            "creation_date": "2026-04-01T14:42:56",
            "last_modification_date": "2026-04-01T14:42:58",
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            "id": 70200,
            "title": "Coding Club for Girls in Biel",
            "slug": "coding-club-for-girls-in-biel-5",
            "event_url": "https://memento.epfl.ch/event/coding-club-for-girls-in-biel-5",
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            "start_date": "2026-02-21",
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            "start_time": "09:30:00",
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            "description": "<p>Eine App programmieren? Ein Computerspiel erfinden? Eine Animation gestalten?<br>\r\nWenn dich eines dieser Dinge interessiert, bist du hier am richtigen Ort! Tausche und teile deine Ideen, lerne zu programmieren und entdecke Informatikberufe. Die <a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/jugendliche/coding-club/\">Coding Club for Girls</a> Workshops sind für Mädchen im Alter von 11 bis 15 Jahren und die Teilnahme ist kostenlos. <br>\r\n<br>\r\nAb der Teilnahme an vier Workshops pro Jahr in Biel wird eine Teilnahmebestätigung ausgehändigt. <br>\r\n<br>\r\n<strong>Ort:</strong>  Haute École Pédagogique BEJUNE, 2503 Biel<br>\r\n<br>\r\n<strong>Datum und Zeit:</strong><br>\r\n<strong>21. Februar 2026 :  09:30 bis 12:00  oder 13:30 bis 16:00 Uhr  // Webdesignerin</strong><br>\r\n<strong>21. März 2026 : 09:30 bis 12:00 oder 13:30 bis 16:00 Uhr  // Pixel Art<br>\r\n25. April 2026 : 09:30 bis 12:00 oder 13:30 bis 16:00 Uhr  // Cyber Security</strong><br>\r\n<br>\r\nDie Inhalte der Workshops sind untenstehend beschrieben.<br>\r\n<br>\r\n<strong>Bedingungen</strong>\r\n</p><ul>\r\n\t<li>Gratis</li>\r\n\t<li><a href=\"https://forms.gle/ToUvUGPKD7cjXwCP8\">Anmeldung unter diesem Link </a></li>\r\n\t<li><a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/teilnahmebedingungen/\">Allgemeine Teilnahmebedingungen EPFL - SPS Aktivitäten</a> </li>\r\n</ul>\r\n<strong>Workshops:<br>\r\nWebdesignerin - Samstag, 21. Februar 2026</strong><br>\r\nEntdecke den Hintergrund einer Webseite und entwerfe deine eigene von A bis Z mit derselben Sprache wie die Profis! An diesem Workshop wirst du mit HTML vertraut und wirst verstehen, wie Webseiten gestaltet wurden und wie weit du selbst gehen kannst.<br>\r\n<br>\r\n<strong>Pixel Art - Samstag, 21. März 2026</strong><br>\r\nEntdecke zwei neue Programmiersprachen, JavaScript und HTML, indem du deine eigenen pixelisierten Kunstwerke gestaltest. Du wirst mit deinem Zeichenprogramm auch ein Rätselspiel für zwei Spielerinnen entwickeln.<br>\r\n<br>\r\n<strong>Cyber Security - Samstag, 25. April 2026</strong><br>\r\nWie kann man sich vom weltweiten Netz schützen? Dir hat man bestimmt schon gesagt: kommuniziere nicht mit Unbekannten, gebe keine persönlichen Angaben an...  Dank diesem Workshop wirst du verstehen, wie Internet funktionniert und wie man Gefahren vorhersehen kann. Du wirst Username- und Passwortgeneratoren programmieren.<br>\r\n<br>\r\n<a href=\"https://forms.gle/ToUvUGPKD7cjXwCP8\"><strong>Anmeldung</strong></a><br>\r\n ",
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